BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Manan Bhatia (Indian Institute of Science\, Bangalore) DTSTART:20200729T090000Z DTEND:20200729T104500Z DTSTAMP:20260421T141437Z UID:BPS/1 DESCRIPTION:Title: Mode rate deviation estimates in stationary last passage percolation.\nby M anan Bhatia (Indian Institute of Science\, Bangalore) as part of Bangalore Probability Seminar\n\n\nAbstract\nThe planar exponential last passage pe rcolation model is an important integrable model in the (1+1) dimensional KPZ universality class. In the first talk\, we introduce the model and its connections to the TASEP and give some examples of the known results for the different initial conditions. In the second technical talk\, we go thr ough a proof of the optimal exponent right tail estimates for the exit tim e for the stationary initial condition\, as well as the upper and lower ta il estimates for the stationary passage time.\n\nIt will be two talks of 4 5 minutes each with a 10-15 minutes break.\n LOCATION:https://researchseminars.org/talk/BPS/1/ END:VEVENT BEGIN:VEVENT SUMMARY:Antar Bandyopadhyay (Indian Statistical Institute\, Delhi) DTSTART:20200812T090000Z DTEND:20200812T095000Z DTSTAMP:20260421T141437Z UID:BPS/2 DESCRIPTION:Title: A La st Progeny Modified Branching Random Walk\nby Antar Bandyopadhyay (Ind ian Statistical Institute\, Delhi) as part of Bangalore Probability Semina r\n\n\nAbstract\nIn this work\, we consider a modification of the usual Br anching Random Walk (BRW)\, where at the n-th step we give certain i.i.d. displacements to each individuals\, which may be different from the drivi ng increment distribution. Depending on the value a parameter\, we classi fy the model in three distinct cases\, namely\, the boundary case\, below the boundary case and above the boundary case. Under very minimal assumpti ons on the underlying point process of the increments\, we show that at th e boundary case\, the maximum displacement converges to a limit after only an appropriate centering\, which is of the form c1 n - c2log n. We give e xplicit formula for the constants c1 and c2 and show that c1 is exactly sa me\, while c2 is 1/3 of the corresponding constants of the usual BRW. We also characterize the limiting distribution. We further show that below th e boundary the logarithmic correction term is absent. For above the bounda ry case\, we have only partial result which indicates a possible existence of the logarithmic correction in the centering with exactly same constan t as that of the classical BRW. Our proofs are based on a novel method of coupling with a more well studied process known as the smoothing transfor mation\, which is used in various non-parametric statistical methods.\n LOCATION:https://researchseminars.org/talk/BPS/2/ END:VEVENT BEGIN:VEVENT SUMMARY:Parthanil Roy (Indian Statistical Institute\, Bangalore) DTSTART:20200812T100000Z DTEND:20200812T104500Z DTSTAMP:20260421T141437Z UID:BPS/3 DESCRIPTION:Title: Grou p measure space construction\, ergodicity and superrigidity for stable ran dom fields\nby Parthanil Roy (Indian Statistical Institute\, Bangalore ) as part of Bangalore Probability Seminar\n\n\nAbstract\nIn this work\, i t is established that the group measure space construction corresponding t o a minimal representation is an invariant of a stationary symmetric $\\al pha$-stable (S$\\alpha$S) random field indexed by any countable group $G$. When $G=\\mathbb{Z}^d$\, we characterize ergodicity of stationary S$\\alp ha$S fields in terms of the central decomposition of this crossed product von Neumann algebra coming from any (not necessarily minimal) Rosinski rep resentation. This shows that ergodicity is a $W^*$-rigid property (in a su itable sense) for this class of fields. All our results have analogues for stationary max-stable random fields as well.\n LOCATION:https://researchseminars.org/talk/BPS/3/ END:VEVENT BEGIN:VEVENT SUMMARY:Hao Wu (Yau Mathematical Science Center\, Tsinghua University) DTSTART:20200826T050000Z DTEND:20200826T064500Z DTSTAMP:20260421T141437Z UID:BPS/4 DESCRIPTION:Title: Cros sing Probabilities in 2D Critical Lattice Models\nby Hao Wu (Yau Mathe matical Science Center\, Tsinghua University) as part of Bangalore Probabi lity Seminar\n\n\nAbstract\nThe planar Ising model is one of the most stud ied lattice models in statistical physics. It was introduced in the 1920s by W. Lenz as a model for magnetic materials. R. Peierls showed in 1936\, in two (and higher) dimensions\, an order-disorder phase transition in fac t occurs at a certain critical temperature. Ever since\, there has been ac tive research to understand the 2D Ising model at criticality\, where it e njoys conformal invariance in the scaling limit. In this talk\, we give c rossing probabilities of multiple interfaces in the critical planar Ising model with alternating boundary conditions. Besides\, we also explain that a similar formula on the crossing probabilities also holds for critical P ercolation and level lines of Gaussian Free Field.\n LOCATION:https://researchseminars.org/talk/BPS/4/ END:VEVENT BEGIN:VEVENT SUMMARY:Joseph Yukich (Lehigh University\, USA) DTSTART:20200923T110000Z DTEND:20200923T124500Z DTSTAMP:20260421T141437Z UID:BPS/5 DESCRIPTION:Title: Conv ex Hulls of Random Point Sets\nby Joseph Yukich (Lehigh University\, U SA) as part of Bangalore Probability Seminar\n\n\nAbstract\nThe convex hul l of a point set is the smallest convex polytope containing the point set. Convex hulls of random points in Euclidean space arise naturally in a wide variety of disciplines\, including optimization\, computational geome try\, statistics\, economics\, and ethology. This talk will survey old a nd new results describing statistics of the convex hull on large data sets . We shall also discuss more recent results concerning the fluctuations an d the scaling limit of the convex hull boundary. This talk is based on joi nt work with Pierre Calka.\n LOCATION:https://researchseminars.org/talk/BPS/5/ END:VEVENT BEGIN:VEVENT SUMMARY:Rahul Roy (Indian Statistical Institute\, Delhi) DTSTART:20201007T090000Z DTEND:20201007T104500Z DTSTAMP:20260421T141437Z UID:BPS/6 DESCRIPTION:Title: On m odels of evolution of species\nby Rahul Roy (Indian Statistical Instit ute\, Delhi) as part of Bangalore Probability Seminar\n\n\nAbstract\nThis talk has two parts. In the first part we discuss the Bak-Sneppen and the\n Guiol-Machado-Schinazi (GMS) models of evolution.\n\nIn the second part of the talk we study the variation of the GMS model introduced by Ben-Ari an d Schinazi (2016). This model is a birth and death model with an individua l at birth being either a mutant with a random fitness parameter in [0\, 1 ] or having one of the existing fitness parameters with uniform probabilit y\; whereas a death event removes the entire population of the least fit s ite. We change this to incorporate the notion of ‘survival of the fittes t’\, by requiring that a non-mutant individual\, at birth\, has a fitnes s according to a preferential attachment mechanism\, i.e.\, it has a fitne ss f with a probability proportional to the size of the population of fitn ess f. Also death just removes one individual at the least fit site. This preferential attachment rule leads to a power law behaviour in the asympto tics\, unlike the exponential behaviour obtained by Ben-Ari and Schinazi ( 2016).\n LOCATION:https://researchseminars.org/talk/BPS/6/ END:VEVENT BEGIN:VEVENT SUMMARY:Manjunath Krishnapur (Indian Institute of Science\, Bangalore) DTSTART:20201021T090000Z DTEND:20201021T110000Z DTSTAMP:20260421T141437Z UID:BPS/7 DESCRIPTION:Title: Two proofs of the KMT theorems\nby Manjunath Krishnapur (Indian Institute of Science\, Bangalore) as part of Bangalore Probability Seminar\n\n\nAbst ract\nThe Komlós-Major-Tusnády theorem for simple symmetric random walk asserts that up to n steps\, its path can be coupled to stay within distan ce log(n) of a Brownian motion run for time n. A second KMT theorem says t hat the empirical distribution function of n i.i.d. uniform random variabl es on [0\,1] can be coupled to stay within log(n)/√n distance of a Brown ian bridge.\n\nAdding the idea of Cauchy criterion to existing proof archi tectures\, we obtain (perhaps) simpler proofs of the above theorems. The f irst proof compares two Binomial distributions by combinatorial methods. T he second proof compares Binomial and hypergeometric distributions among themselves by coupling Markov chains with these as stationary distribution s. This is based on Chatterjee's proof via a form of Stein's method.\n\nTh e first lecture will give an overview and the essence of the first proof. The second lecture will give an account of the second proof. Despite the s tatement of the main results\, much of the lecture should be accessible ( without knowing about Brownian motion) to those who know Markov chains.\n LOCATION:https://researchseminars.org/talk/BPS/7/ END:VEVENT BEGIN:VEVENT SUMMARY:Ryoki Fukushima (Univ. Tsukuba\, Japan) DTSTART:20201104T050000Z DTEND:20201104T070000Z DTSTAMP:20260421T141437Z UID:BPS/10 DESCRIPTION:Title: Ann ealed random walk conditioned on survival among Bernoulli obstacles\nb y Ryoki Fukushima (Univ. Tsukuba\, Japan) as part of Bangalore Probability Seminar\n\n\nAbstract\nI will present two recent results on a discrete ti me random walk conditioned to avoid Bernoulli obstacles on the d-dimension al integer lattice obtained in joint works with Jian Ding\, Rongfeng Sun a nd Changji Xu. The first result on this model dates back to a famous work by Donsker and Varadhan on the Wiener sausage in 1975. Since then\, it has been intensively studied and various localization results have been prove d. In particular\, the random walk is known to localize in a ball of sub-d iffusive size under the annealed law. Our first result gives a more detail ed geometric description of the range of the random walk. More precisely\, we showed that it completely fills the ball where the walk is localized\, and in addition we got a sharp estimate on the size of its boundary. \n\n Our second result is about the response to an external force. If we give a bias to the random walk\, then the model is known to undergo a phase tran sition: for a large bias\, the walk is ballistic whereas for a small bias\ , it is sub-ballistic. This phase transition was proved by Sznitman and la ter\, Ioffe and Velenik studied the ballistic phase in detail. In the sub- ballistic phase\, physicists conjectured that the walk is localized in a s ub-diffusive scale as in the unbiased case\, but it has not been proved. W e prove this conjecture with a precise information on the behavior of whol e path.\n LOCATION:https://researchseminars.org/talk/BPS/10/ END:VEVENT BEGIN:VEVENT SUMMARY:Dmitry Belyaev (Univ. Oxford\, UK) DTSTART:20200916T090000Z DTEND:20200916T094500Z DTSTAMP:20260421T141437Z UID:BPS/11 DESCRIPTION:Title: On the number of level sets of smooth Gaussian fields - I\nby Dmitry Bely aev (Univ. Oxford\, UK) as part of Bangalore Probability Seminar\n\n\nAbst ract\nLevel sets of smooth Gaussian fields appear in many areas of mathema tics. They have numerous applications outside of mathematics from astrophy sics to oceanology to biology. Probably the first significant progress in the study of level lines came in 1940s when Kac and Rice developed formula s that allow to compute the expected number of roots of a random function in 1d. These formulas can be generalised to higher dimension where they al low to compute the expected volume of level sets. Unfortunately\, these fo rmulas do not allow to study the number of level lines since it is a non-l ocal quantity which can not be written as a Kac-Rice-type integral formula . In this talk we will discuss recent progress in the study of the number of level lines for smooth Gaussian fields. \n\nIn the first part of the ta lk D. Belyaev will give a gentle introduction to the area and give a broad overview of recent results. In particular\, he will describe how the numb er of level lines depends on the level. This allows to show that the expec ted number of lines depends (almost) smoothly on the level and allows to g ive a low bound on the fluctuation of the number of level lines. In the se cond part S. Muirhead will explain in more details the ideas behind these results and will sketch the proof of the variance bound.The talk is based on a series of papers by D. Belyaev\, M. McAuley and S. Muirhead.\n LOCATION:https://researchseminars.org/talk/BPS/11/ END:VEVENT BEGIN:VEVENT SUMMARY:Stephen Muirhead (Univ. Melbourne\, Australia) DTSTART:20200916T100000Z DTEND:20200916T104500Z DTSTAMP:20260421T141437Z UID:BPS/12 DESCRIPTION:Title: On the number of level sets of smooth Gaussian fields - II\nby Stephen Mu irhead (Univ. Melbourne\, Australia) as part of Bangalore Probability Semi nar\n\n\nAbstract\nLevel sets of smooth Gaussian fields appear in many are as of mathematics. They have numerous applications outside of mathematics from astrophysics to oceanology to biology. Probably the first significant progress in the study of level lines came in 1940s when Kac and Rice deve loped formulas that allow to compute the expected number of roots of a ran dom function in 1d. These formulas can be generalised to higher dimension where they allow to compute the expected volume of level sets. Unfortunate ly\, these formulas do not allow to study the number of level lines since it is a non-local quantity which can not be written as a Kac-Rice-type int egral formula. In this talk we will discuss recent progress in the study o f the number of level lines for smooth Gaussian fields. \n\nIn the first p art of the talk D. Belyaev will give a gentle introduction to the area and give a broad overview of recent results. In particular\, he will describe how the number of level lines depends on the level. This allows to show t hat the expected number of lines depends (almost) smoothly on the level an d allows to give a low bound on the fluctuation of the number of level lin es. In the second part S. Muirhead will explain in more details the ideas behind these results and will sketch the proof of the variance bound.The t alk is based on a series of papers by D. Belyaev\, M. McAuley and S. Muirh ead.\n LOCATION:https://researchseminars.org/talk/BPS/12/ END:VEVENT BEGIN:VEVENT SUMMARY:Radoslaw Adamczak (Univ. Warsaw\, Poland) DTSTART:20201202T090000Z DTEND:20201202T110000Z DTSTAMP:20260421T141437Z UID:BPS/13 DESCRIPTION:Title: Fun ctional inequalities and moment estimates\nby Radoslaw Adamczak (Univ. Warsaw\, Poland) as part of Bangalore Probability Seminar\n\n\nAbstract\n I will present moment estimates\, which can be obtained by means of functi onal inequalities\, from the classical work due to Aida and Stroock from t he 1990s\, through generalizations of the Efron-Stein inequality for funct ions of independent random variables by Boucheron-Bousquet-Lugosi-Massart (2005) to more recent estimates obtained with various coauthors\n LOCATION:https://researchseminars.org/talk/BPS/13/ END:VEVENT BEGIN:VEVENT SUMMARY:D. Yogeshwaran (Indian Statistical Institute\, Bangalore) DTSTART:20201125T090000Z DTEND:20201125T110000Z DTSTAMP:20260421T141437Z UID:BPS/14 DESCRIPTION:Title: Sha rp phase transition and noise sensitivity in continuum percolation via con tinuous time decision trees.\nby D. Yogeshwaran (Indian Statistical In stitute\, Bangalore) as part of Bangalore Probability Seminar\n\n\nAbstrac t\nProofs of sharp phase transition and noise sensitivity in percolation \ nhave been significantly simplified by the use of randomized algorithms \n via the OSSS (O'Donnell\, Saks\, Schramm and Servedio) variance inequality \nand the Schramm-Steif inequality. In a joint work with Giovanni Peccati \nand Guenter Last\, we prove analogues of these inequalities for a \nPois son point process. This talk will be about these two inequalities \nand th eir applications to continuum percolation. \n\nIn the first talk\, we shal l first introduce the Poisson Boolean \nmodel and continuum percolation. T hen\, we will show how\nsharp phase transition in the Poisson Boolean mode l is derived via \nthe Poisson OSSS inequality. We shall also indicate the proof of the \nPoisson OSSS inequality. Time-permitting\, we will mention \napplications to other models such as k-percolation and confetti \nperco lation.\n\nIn the second talk\, we will see how noise sensitivity and \nex istence of exceptional times at criticality for crossing events in \nthe d ynamical Poisson Boolean model are derived via the Schramm-Steif \ninequal ity for Poisson processes. We shall also discuss the \nSchramm-Steif inequ ality very briefly. \n\nExcept some of the basics on Poisson process and continuum percolation\, \nthe two talks will be somewhat independent.\n LOCATION:https://researchseminars.org/talk/BPS/14/ END:VEVENT BEGIN:VEVENT SUMMARY:Siva Athreya (Indian Statistical Institute\, Bangalore) DTSTART:20201209T090000Z DTEND:20201209T094500Z DTSTAMP:20260421T141437Z UID:BPS/15 DESCRIPTION:Title: Ser o-Survey in Karnataka State: Summary\, Design\, and Statistical Methodol ogy\nby Siva Athreya (Indian Statistical Institute\, Bangalore) as par t of Bangalore Probability Seminar\n\n\nAbstract\nThe state of Karnataka c onducted a survey to estimate the total COVID-19 burden in the state betwe en September 03-16\, 2020. The survey was unique in two main aspects\, na mely\, it jointly estimated both current and past infection in the state a nd secondly the survey covered \nthe entire geographical region of the sta te\, a first in India.\n\nWe shall discuss the design of the survey\, prov ide a brief summary of the findings\, and discuss in detail the probabilit y models/statistical methodology used to obtain the estimates.\n LOCATION:https://researchseminars.org/talk/BPS/15/ END:VEVENT BEGIN:VEVENT SUMMARY:Rajesh Sundaresan ((Indian Institute of Science\, Bangalore) DTSTART:20201209T100000Z DTEND:20201209T104500Z DTSTAMP:20260421T141437Z UID:BPS/16 DESCRIPTION:Title: Ser o-Survey in Karnataka State: Summary\, Design\, and Statistical Methodol ogy\nby Rajesh Sundaresan ((Indian Institute of Science\, Bangalore) a s part of Bangalore Probability Seminar\n\n\nAbstract\nThe state of Karnat aka conducted a survey to estimate the total COVID-19 burden in the state between September 03-16\, 2020. The survey was unique in two main aspects \, namely\, it jointly estimated both current and past infection in the st ate and secondly the survey covered \nthe entire geographical region of th e state\, a first in India.\n\nWe shall discuss the design of the survey\, provide a brief summary of the findings\, and discuss in detail the proba bility models/statistical methodology used to obtain the estimates.\n LOCATION:https://researchseminars.org/talk/BPS/16/ END:VEVENT BEGIN:VEVENT SUMMARY:Kerrie Mengersen (Queensland University of Technology\, Australia) DTSTART:20210127T043000Z DTEND:20210127T061500Z DTSTAMP:20260421T141437Z UID:BPS/17 DESCRIPTION:Title: Bay esian Modelling and Analysis of Challenging Data\nby Kerrie Mengersen (Queensland University of Technology\, Australia) as part of Bangalore Pro bability Seminar\n\n\nAbstract\nPCM-2019-20\n\nhttps://www.isibang.ac.in/~ statmath/pcm2019/\n\nProfessor Kerrie Mengersen\nScience and Engineering F aculty\, School of Mathematical Sciences\nQueensland University of Technol ogy (QUT)\n(https://staff.qut.edu.au/staff/k.mengersen)\n\nwill deliver th e P.C. Mahalanobis Memorial Lectures 2019-20 on\n\nBayesian Modelling and Analysis of Challenging Data\n\nDate: January 27th\, 2021\nTime: 11:00-11: 45am\n\nLecture 1: Bayesian Modelling and Analysis of Challenging Data\nId entifying the Intrinsic Dimension of High-Dimensional Data\n\nAbstract: On e of the challenges of high-dimensional data is\nidentifying the true info rmation contained therein. In this\npresentation\, I will describe some ap proaches that we have developed\nto address this challenge. These approach es include Bayesian methods\nof matrix factorisation\, intrinsic dimension and structured variable\nselection. This discussion will be set in the co ntext of substantive\ncase studies in image analysis\, sport and genomics. \n\nDate: January 27th\, 2021\nTime: 12:00-12:45pm\n\nLecture 2: Bayesian Modelling and Analysis of Challenging Data Finding\nPatterns in Highly Str uctured Spatio-Temporal Data\n\nAbstract: Many forms of current data are i ndexed by space and/or\ntime. Often these space-time relationships are hig hly\nstructured. Examples include data collected across networks of\nstrea ms\, multi-state data collected over time\, and multivariate\nresponses co llected at small area level across a geographic space. In\nthis presentati on\, I will describe some of our approaches to Bayesian\nmodelling and ana lysis of these types of data. Two particular issues\nwill be discussed. Th e first is the role of priors in spatial models\nand hidden Markov models. The second is the detection of anomalies for\nevent identification and to increase the trustworthiness of the data.\n\n\nThe lectures were original ly due to held in March 2020 but are now being\nheld online via Zoom platf orm.\n\nhttps://us02web.zoom.us/j/88118975864?pwd=cFRmWXMreWdiLzR5VGlCYXBC bE1WZz09\n LOCATION:https://researchseminars.org/talk/BPS/17/ END:VEVENT BEGIN:VEVENT SUMMARY:Kerrie Mengersen (Queensland University of Technology\, Australia) DTSTART:20210129T043000Z DTEND:20210129T061500Z DTSTAMP:20260421T141437Z UID:BPS/18 DESCRIPTION:Title: Bay esian Modelling and Analysis of Challenging Data\nby Kerrie Mengersen (Queensland University of Technology\, Australia) as part of Bangalore Pro bability Seminar\n\n\nAbstract\nPCM-2019-20\n\nhttps://www.isibang.ac.in/~ statmath/pcm2019/\n\nProfessor Kerrie Mengersen\nScience and Engineering F aculty\, School of Mathematical Sciences\nQueensland University of Technol ogy (QUT)\n(https://staff.qut.edu.au/staff/k.mengersen)\n\nwill deliver th e P.C. Mahalanobis Memorial Lectures 2019-20 on\n\nBayesian Modelling and Analysis of Challenging Data\n\nDate: January 29th\, 2021\nTime: 11:00-11: 45am\n\nLecture 3: Bayesian Modelling and Analysis of Challenging Data Des cribing\nSystems of Data\n\nAbstract: A common challenge is to analyse dat a as part of a\nsystem. In this presentation\, I describe a number of Baye sian\napproaches to modelling such data\, using as motivation case studies in\nneurology\, ecology and industry. These case studies focus on\nunders tanding changes in the brain associated with a degenerative\ndisease\, and suggesting optimal dredgingstrategies for conservation of\nseagrass. The techniques employed include Bayesian wombling and\ndynamic Bayesian networ ks.\n\nDate: January 29th\, 2021\nTime: 12:00-12:45pm\n\nLecture 4: Bayesi an Modelling and Analysis of Challenging Data Making New\nSources of Data Trustworthy\n\nAbstract: Evidence-based decisions depend critically on tru stworthy\ndata. Two forms of data that have been brought into question in recent\ntimes are sensor data and citizen science data. Sensors are a key\ ncomponent of IoT and have created a step-change in our ability to\nmonito r systems. However\, they are often subject to technical\nanomalies that r aise concerns about the validity of their data and\nsignals. Citizen scien ce is also growing in utility and interest in\nmany areas\, but often suff ers from concerns about the credibility the\ninformation provided by commu nity members. In this presentation\, I\nwill describe some new approaches to resolving some of these\nconcerns. These include new methods for anomal y detection in\nhigh-dimensional streaming time series\, and Bayesian mode ls for\nestimating the latent ability of citizens taking into account the\ ndifficulty of the tasks. This work has been developed in collaboration\nw ith a number of teams working on challenges in ecology and industry\;\nthe se teams will be acknowledged and the associated challenges\ndiscussed dur ing the presentation.\n\n\nThe lectures were originally due to held in Mar ch 2020 but are now being\nheld online via Zoom platform.\n\nhttps://us02w eb.zoom.us/j/88118975864?pwd=cFRmWXMreWdiLzR5VGlCYXBCbE1WZz09\n LOCATION:https://researchseminars.org/talk/BPS/18/ END:VEVENT BEGIN:VEVENT SUMMARY:Alon Nishry (Tel-Aviv University\, Israel) DTSTART:20210201T090000Z DTEND:20210201T094500Z DTSTAMP:20260421T141437Z UID:BPS/19 DESCRIPTION:Title: Gau ssian complex zeros: conditional distribution on rare events\nby Alon Nishry (Tel-Aviv University\, Israel) as part of Bangalore Probability Sem inar\n\n\nAbstract\nThe zero process of the Gaussian Entire Function is a natural example of a two-dimensional random point configuration whose dist ribution is invariant under rigid motions of the plane. Another well-studi ed example is the infinite Ginibre ensemble. Due to non-trivial correlatio ns\, the features of these two processes are quite different from the ones of the homogeneous Poisson point process. For this reason\, these process es are of interest to analysts\, probabilists\, and mathematical physicist s.\n\nSome particularly interesting statistical phenomena to study are rar e events\, when the number of points in a certain large domain is very dif ferent from its expected value. An important example is the ‘hole event ’\, when there are no points at all. For the Ginibre ensemble\, the hole event can be studied using some classical tools from potential theory. Th is is no longer true for complex zeros\, and in this talk I will mention s ome of the challenges and describe new results.\n\nBased on joint works wi th S. Ghosh (NUS) and A. Wennman (Tel Aviv)\n LOCATION:https://researchseminars.org/talk/BPS/19/ END:VEVENT BEGIN:VEVENT SUMMARY:Aron Wenmann (Tel-Aviv University\, Israel) DTSTART:20210201T100000Z DTEND:20210201T104500Z DTSTAMP:20260421T141437Z UID:BPS/20 DESCRIPTION:Title: The forbidden region for random zeros: appearance of quadrature domains\n by Aron Wenmann (Tel-Aviv University\, Israel) as part of Bangalore Probab ility Seminar\n\n\nAbstract\nWe consider the hole event for Gaussian compl ex zeros. As the size of the hole increases\, the density of zeros vanishe s\, not just inside the hole\, but also on a macroscopic region beyond the (rescaled) hole - a 'forbidden region' emerges. Surprisingly\, the shape of this region is rigid under perturbations of the hole.\n\nI will discuss the shape of the forbidden region for general simply connected holes. I p lan to explain how to study the limiting zero density through a constraine d variational problem\, and touch upon a curious emergence of quadrature d omains from potential theory.\n LOCATION:https://researchseminars.org/talk/BPS/20/ END:VEVENT BEGIN:VEVENT SUMMARY:M. E. Lakshmi Priya (Indian Institute of Science\, Bangalore) DTSTART:20210215T090000Z DTEND:20210215T094500Z DTSTAMP:20260421T141437Z UID:BPS/21 DESCRIPTION:Title: Ove rcrowding estimates for nodal volume of stationary Gaussian processes (SGP s) on R^d\nby M. E. Lakshmi Priya (Indian Institute of Science\, Banga lore) as part of Bangalore Probability Seminar\n\n\nAbstract\nWe consider centered SGPs on Euclidean spaces R^d and study their nodal volume in [0\, T]^d\, for T>0. From earlier studies\, we know the following statistics fo r nodal volume of SGPs under varying assumptions on their spectral measure s: expectation\, variance asymptotics\, CLT\, exponential concentration (o nly for d=1)\, and finiteness of moments. \n\nWe study the unlikely event of overcrowding of the nodal set in [0\,T]^d\; this is the event that the volume of the nodal set in [0\,T]^d is much larger than its expected value . Under some mild assumptions on the spectral measure\, we obtain estimate s for the overcrowding event's probability. We first get overcrowding esti mates for the zero count of SGPs on R. In higher dimensions\, we consider Crofton's formula\, which gives the volume of the nodal set in terms of th e number of intersections of the nodal set with all lines in R^d. We discr etize this formula to get a more workable version of it and\, in a sense\, reduce the overcrowding problem in higher dimensions to the one-dimension al case.\n LOCATION:https://researchseminars.org/talk/BPS/21/ END:VEVENT BEGIN:VEVENT SUMMARY:Subhajit Ghosh (Indian Institute of Science\, Bangalore) DTSTART:20210215T100000Z DTEND:20210215T104500Z DTSTAMP:20260421T141437Z UID:BPS/22 DESCRIPTION:Title: Tot al variation cutoff for the flip-transpose top with random shuffle\nby Subhajit Ghosh (Indian Institute of Science\, Bangalore) as part of Banga lore Probability Seminar\n\n\nAbstract\nWe consider a random walk on the h yperoctahedral group $B_n$ generated by the signed permutations of the for m $(i\,n)$ and $(-i\,n)$ for $1\\leq i\\leq n$. We call this the \\emph{fl ip-transpose top with random shuffle} on $B_n$. We find the spectrum of th e transition probability matrix for this shuffle. We prove that this shuff le exhibits the total variation cutoff phenomenon with cutoff time $n\\log n$. We also show that a biased variant of this shuffle exhibits the total variation cutoff with the same cutoff time.\n LOCATION:https://researchseminars.org/talk/BPS/22/ END:VEVENT BEGIN:VEVENT SUMMARY:Vladimir Vovk (University of London\, U.K.) DTSTART:20210315T093000Z DTEND:20210315T101500Z DTSTAMP:20260421T141437Z UID:BPS/23 DESCRIPTION:Title: Mar tingales in the foundations of statistics\nby Vladimir Vovk (Universit y of London\, U.K.) as part of Bangalore Probability Seminar\n\n\nAbstract \nhttps://www.isibang.ac.in/~statmath/pcm2020/\n\nMartingales in the found ations of statistics\nDate: March 15th\, 2021\nTime: 15:00-15:45 IST\n\n\n Abstract: Traditional methods of testing statistical hypotheses have been developed for the batch setting\, in the terminology of machine learning: given a batch of data\, statisticians typically compute measures of disagr eement\, such as p-values or Bayes factors\, between a null hypothesis and the data. An alternative that is popular in machine learning is the onlin e setting\, in which the items of data (observations ) keep arriving seque ntially. In this introductory lecture I will explain the role of martingal es\, in the form of test martingales\, in online hypothesis testing and di scuss their applications in the foundations of probability and statistics. \n\nMultiple hypothesis testing with e-values\nDate: March 15th\, 2021\nTi me: 16:00-16:45 IST\n\nAbstract: It is interesting that test martingales d o not trivialize in the case of only one observation. In fact\, they provi de a useful alternative\, sometimes called e-values\, to the standard stat istical notion of p-values. The most important mathematical advantage of e -values over p-values is that the average of e-values is always an e-value . This property is valuable in multiple hypothesis testing\, which will be the topic of this lecture.\n\nConformal prediction\nDate: March 19th\, 20 21\nTime: 15:00-15:45 IST\n\nAbstract: Mainstream machine learning\, despi te its recent successes\, has a serious drawback: while its state-of-the-a rt algorithms often produce excellent predictions\, they do not provide me asures of their accuracy and reliability that would be both practically us eful and provably valid. On the other hand\, such measures are commonplace in statistics. Conformal prediction adapts rank tests\, popular in nonpar ametric statistics\, to testing the IID assumption (the observations being independent and identically distributed)\, which is the standard assumpti on made in machine learning. This gives us practical measures\, provably v alid under the IID assumption\, of the accuracy and reliability of predict ions produced by traditional and recent machine-learning algorithms. In th is lecture I will give a brief review of conformal prediction.\n\nConforma l hypothesis testing\nDate: March 19th\, 2021\nTime: 16:00-16:45 IST\n\nAb stract: An interesting application of conformal prediction is the existenc e of exchangeability martingales\, i.e.\, random processes that are test m artingales under any exchangeable probability measure. In particular\, the y are martingales whenever the observations are IID. The topics of this la st lecture in this series will be the construction of exchangeability mart ingales and their use for different kinds of change detection\, including detecting a point at which the IID assumption becomes violated and detecti ng concept shift.\n LOCATION:https://researchseminars.org/talk/BPS/23/ END:VEVENT BEGIN:VEVENT SUMMARY:Vladimir Vovk (University of London\, U.K.) DTSTART:20210315T103000Z DTEND:20210315T111500Z DTSTAMP:20260421T141437Z UID:BPS/24 DESCRIPTION:Title: Mul tiple hypothesis testing with e-values\nby Vladimir Vovk (University o f London\, U.K.) as part of Bangalore Probability Seminar\n\n\nAbstract\nh ttps://www.isibang.ac.in/~statmath/pcm2020/\n\nMartingales in the foundati ons of statistics\nDate: March 15th\, 2021\nTime: 15:00-15:45 IST\n\n\nAbs tract: Traditional methods of testing statistical hypotheses have been dev eloped for the batch setting\, in the terminology of machine learning: giv en a batch of data\, statisticians typically compute measures of disagreem ent\, such as p-values or Bayes factors\, between a null hypothesis and th e data. An alternative that is popular in machine learning is the online s etting\, in which the items of data (observations ) keep arriving sequenti ally. In this introductory lecture I will explain the role of martingales\ , in the form of test martingales\, in online hypothesis testing and discu ss their applications in the foundations of probability and statistics.\n\ nMultiple hypothesis testing with e-values\nDate: March 15th\, 2021\nTime: 16:00-16:45 IST\n\nAbstract: It is interesting that test martingales do n ot trivialize in the case of only one observation. In fact\, they provide a useful alternative\, sometimes called e-values\, to the standard statist ical notion of p-values. The most important mathematical advantage of e-va lues over p-values is that the average of e-values is always an e-value. T his property is valuable in multiple hypothesis testing\, which will be th e topic of this lecture.\n\nConformal prediction\nDate: March 19th\, 2021\ nTime: 15:00-15:45 IST\n\nAbstract: Mainstream machine learning\, despite its recent successes\, has a serious drawback: while its state-of-the-art algorithms often produce excellent predictions\, they do not provide measu res of their accuracy and reliability that would be both practically usefu l and provably valid. On the other hand\, such measures are commonplace in statistics. Conformal prediction adapts rank tests\, popular in nonparame tric statistics\, to testing the IID assumption (the observations being in dependent and identically distributed)\, which is the standard assumption made in machine learning. This gives us practical measures\, provably vali d under the IID assumption\, of the accuracy and reliability of prediction s produced by traditional and recent machine-learning algorithms. In this lecture I will give a brief review of conformal prediction.\nConformal hyp othesis testing\nDate: March 19th\, 2021\nTime: 16:00-16:45 IST\n\nAbstrac t: An interesting application of conformal prediction is the existence of exchangeability martingales\, i.e.\, random processes that are test martin gales under any exchangeable probability measure. In particular\, they are martingales whenever the observations are IID. The topics of this last le cture in this series will be the construction of exchangeability martingal es and their use for different kinds of change detection\, including detec ting a point at which the IID assumption becomes violated and detecting co ncept shift.\n LOCATION:https://researchseminars.org/talk/BPS/24/ END:VEVENT BEGIN:VEVENT SUMMARY:Vladimir Vovk (University of London\, U.K.) DTSTART:20210319T093000Z DTEND:20210319T101500Z DTSTAMP:20260421T141437Z UID:BPS/25 DESCRIPTION:Title: Con formal prediction\nby Vladimir Vovk (University of London\, U.K.) as p art of Bangalore Probability Seminar\n\n\nAbstract\nhttps://www.isibang.ac .in/~statmath/pcm2020/\n\nMartingales in the foundations of statistics\nDa te: March 15th\, 2021\nTime: 15:00-15:45 IST\n\n\nAbstract: Traditional me thods of testing statistical hypotheses have been developed for the batch setting\, in the terminology of machine learning: given a batch of data\, statisticians typically compute measures of disagreement\, such as p-value s or Bayes factors\, between a null hypothesis and the data. An alternativ e that is popular in machine learning is the online setting\, in which the items of data (observations ) keep arriving sequentially. In this introdu ctory lecture I will explain the role of martingales\, in the form of test martingales\, in online hypothesis testing and discuss their applications in the foundations of probability and statistics.\n\nMultiple hypothesis testing with e-values\nDate: March 15th\, 2021\nTime: 16:00-16:45 IST\n\nA bstract: It is interesting that test martingales do not trivialize in the case of only one observation. In fact\, they provide a useful alternative\ , sometimes called e-values\, to the standard statistical notion of p-valu es. The most important mathematical advantage of e-values over p-values is that the average of e-values is always an e-value. This property is valua ble in multiple hypothesis testing\, which will be the topic of this lectu re.\n\nConformal prediction\nDate: March 19th\, 2021\nTime: 15:00-15:45 IS T\n\nAbstract: Mainstream machine learning\, despite its recent successes\ , has a serious drawback: while its state-of-the-art algorithms often prod uce excellent predictions\, they do not provide measures of their accuracy and reliability that would be both practically useful and provably valid. On the other hand\, such measures are commonplace in statistics. Conforma l prediction adapts rank tests\, popular in nonparametric statistics\, to testing the IID assumption (the observations being independent and identic ally distributed)\, which is the standard assumption made in machine learn ing. This gives us practical measures\, provably valid under the IID assum ption\, of the accuracy and reliability of predictions produced by traditi onal and recent machine-learning algorithms. In this lecture I will give a brief review of conformal prediction.\nConformal hypothesis testing\nDate : March 19th\, 2021\nTime: 16:00-16:45 IST\n\nAbstract: An interesting app lication of conformal prediction is the existence of exchangeability marti ngales\, i.e.\, random processes that are test martingales under any excha ngeable probability measure. In particular\, they are martingales whenever the observations are IID. The topics of this last lecture in this series will be the construction of exchangeability martingales and their use for different kinds of change detection\, including detecting a point at which the IID assumption becomes violated and detecting concept shift.\n LOCATION:https://researchseminars.org/talk/BPS/25/ END:VEVENT BEGIN:VEVENT SUMMARY:Vladimir Vovk (University of London\, U.K.) DTSTART:20210319T103000Z DTEND:20210319T111500Z DTSTAMP:20260421T141437Z UID:BPS/26 DESCRIPTION:Title: Con formal hypothesis testing\nby Vladimir Vovk (University of London\, U. K.) as part of Bangalore Probability Seminar\n\n\nAbstract\nhttps://www.is ibang.ac.in/~statmath/pcm2020/\n\nMartingales in the foundations of statis tics\nDate: March 15th\, 2021\nTime: 15:00-15:45 IST\n\n\nAbstract: Tradit ional methods of testing statistical hypotheses have been developed for th e batch setting\, in the terminology of machine learning: given a batch of data\, statisticians typically compute measures of disagreement\, such as p-values or Bayes factors\, between a null hypothesis and the data. An al ternative that is popular in machine learning is the online setting\, in w hich the items of data (observations ) keep arriving sequentially. In this introductory lecture I will explain the role of martingales\, in the form of test martingales\, in online hypothesis testing and discuss their appl ications in the foundations of probability and statistics.\n\nMultiple hyp othesis testing with e-values\nDate: March 15th\, 2021\nTime: 16:00-16:45 IST\n\nAbstract: It is interesting that test martingales do not trivialize in the case of only one observation. In fact\, they provide a useful alte rnative\, sometimes called e-values\, to the standard statistical notion o f p-values. The most important mathematical advantage of e-values over p-v alues is that the average of e-values is always an e-value. This property is valuable in multiple hypothesis testing\, which will be the topic of th is lecture.\n\nConformal prediction\nDate: March 19th\, 2021\nTime: 15:00- 15:45 IST\n\nAbstract: Mainstream machine learning\, despite its recent su ccesses\, has a serious drawback: while its state-of-the-art algorithms of ten produce excellent predictions\, they do not provide measures of their accuracy and reliability that would be both practically useful and provabl y valid. On the other hand\, such measures are commonplace in statistics. Conformal prediction adapts rank tests\, popular in nonparametric statisti cs\, to testing the IID assumption (the observations being independent and identically distributed)\, which is the standard assumption made in machi ne learning. This gives us practical measures\, provably valid under the I ID assumption\, of the accuracy and reliability of predictions produced by traditional and recent machine-learning algorithms. In this lecture I wil l give a brief review of conformal prediction.\nConformal hypothesis testi ng\nDate: March 19th\, 2021\nTime: 16:00-16:45 IST\n\nAbstract: An interes ting application of conformal prediction is the existence of exchangeabili ty martingales\, i.e.\, random processes that are test martingales under a ny exchangeable probability measure. In particular\, they are martingales whenever the observations are IID. The topics of this last lecture in this series will be the construction of exchangeability martingales and their use for different kinds of change detection\, including detecting a point at which the IID assumption becomes violated and detecting concept shift.\ n LOCATION:https://researchseminars.org/talk/BPS/26/ END:VEVENT BEGIN:VEVENT SUMMARY:Martin Barlow (University of British Columbia\, Canada) DTSTART:20210316T093000Z DTEND:20210316T111500Z DTSTAMP:20260421T141437Z UID:BPS/27 DESCRIPTION:Title: Har nack inequalities - from PDE to random graphs\nby Martin Barlow (Unive rsity of British Columbia\, Canada) as part of Bangalore Probability Semin ar\n\n\nAbstract\nhttps://www.isibang.ac.in/~statmath/amml20/\n\nA major p roblem in PDE\, solved independently in the late 1950s by de Giorgi\, Moser and Nash\, was the regularity of solutions to second order divergenc e form equations. Moser's approach was to use a Harnack inequality\, w hich can be understood in probabilistic terms.a \n\n These PDE metho ds are very versatile\, and have been extended to manifolds\, general metric spaces\, and graphs. They give continuity results for harmonic func tions\, and lead to estimates of the transition density of Markov processe s. Of particular importance is the fact that the PDE approach is rob ust enough to able to handle small local perturbations of the space. \n \n\n These lectures will review this progress\, and will present applica tions of Harnack inequalities to random walks on random graphs. \n\n \ n\nDate: March 16th\, 2021\n\n Lecture 1 \n Tim e: 15:00-15:45\, IST \n \n Lecture 2 \n Time: 16:00-16:45\, IST \n \nDate: March 18th\, 20 21\n\n Lecture 1 \n Time: 15:00-15:45\, IST \n \n Lecture 2 \n Time: 16:00-16:4 5\, IST\n LOCATION:https://researchseminars.org/talk/BPS/27/ END:VEVENT BEGIN:VEVENT SUMMARY:Martin Barlow (University of British Columbia\, Canada) DTSTART:20210318T093000Z DTEND:20210318T101500Z DTSTAMP:20260421T141437Z UID:BPS/29 DESCRIPTION:Title: Har nack inequalities - from PDE to random graphs\nby Martin Barlow (Unive rsity of British Columbia\, Canada) as part of Bangalore Probability Semin ar\n\n\nAbstract\nhttps://www.isibang.ac.in/~statmath/amml20/\n\nA major p roblem in PDE\, solved independently in the late 1950s by de Giorgi\, Moser and Nash\, was the regularity of solutions to second order divergenc e form equations. Moser's approach was to use a Harnack inequality\, w hich can be understood in probabilistic terms.a \n\n These PDE metho ds are very versatile\, and have been extended to manifolds\, general metric spaces\, and graphs. They give continuity results for harmonic func tions\, and lead to estimates of the transition density of Markov processe s. Of particular importance is the fact that the PDE approach is rob ust enough to able to handle small local perturbations of the space. \n \n\n These lectures will review this progress\, and will present applica tions of Harnack inequalities to random walks on random graphs. \n\n \ n\nDate: March 16th\, 2021\n\n Lecture 1 \n Tim e: 15:00-15:45\, IST \n \n Lecture 2 \n Time: 16:00-16:45\, IST \n \nDate: March 18th\, 20 21\n\n Lecture 1 \n Time: 15:00-15:45\, IST \n \n Lecture 2 \n Time: 16:00-16:4 5\, IST\n LOCATION:https://researchseminars.org/talk/BPS/29/ END:VEVENT BEGIN:VEVENT SUMMARY:Justin Salez (Univ. Paris-Dauphine\, Paris) DTSTART:20210412T090000Z DTEND:20210412T110000Z DTSTAMP:20260421T141437Z UID:BPS/30 DESCRIPTION:Title: An entropic interpretation of the cutoff phenomenon for finite Markov chains< /a>\nby Justin Salez (Univ. Paris-Dauphine\, Paris) as part of Bangalore P robability Seminar\n\n\nAbstract\nThe cutoff phenomenon is a sharp phase t ransition in the convergence to equilibrium of certain Markov chains. Disc overed by Aldous\, Diaconis and Shahshahani in the context of card shuffl ing\, it has since then been established on a variety of examples. However \, proving cutoff remains a delicate affair\, which requires a very detail ed knowledge of the chain. Identifying the general mechanisms underlying t his phase transition\, without having to pinpoint its precise location\, r emains one of the most fundamental open problems in the area of mixing tim es.\n\nIn the first part of the lecture\, I will provide a self-contained introduction to this beautiful question\, and present some classical examp les. In the second part\, I will discuss a recent interpretation of the cu toff phenomenon in terms of concentration of entropy\, and show how this c an be used to deduce cutoff for a broad class of Markov chains with non-ne gative curvature\, including random walks on abelian Cayley expanders.\n LOCATION:https://researchseminars.org/talk/BPS/30/ END:VEVENT BEGIN:VEVENT SUMMARY:Mohammud Foondun (Univ. Strathclyde\, U. K.) DTSTART:20210419T090000Z DTEND:20210419T094500Z DTSTAMP:20260421T141437Z UID:BPS/31 DESCRIPTION:by Mohammud Foondun (Univ. Strathclyde\, U. K.) as part of Ban galore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/31/ END:VEVENT BEGIN:VEVENT SUMMARY:Kunwoo Kim (POSTECH\, Korea) DTSTART:20210419T100000Z DTEND:20210419T104500Z DTSTAMP:20260421T141437Z UID:BPS/32 DESCRIPTION:Title: Pha se Analysis for a family of Stochastic Reaction-Diffusion Equations\nb y Kunwoo Kim (POSTECH\, Korea) as part of Bangalore Probability Seminar\n\ n\nAbstract\nWe consider a family of stochastic reaction-diffusion equatio ns driven by space-time white noise. The reaction term belongs to a large family of functions that includes Fisher-KPP nonlinearities [V (x) = x(1 − x)] as well as Allen-Cahn potentials [V (x) = x(1 − x)(1 + x)] . We show that (i) if the noise intensity is large\, our stochastic PDE has the unique invariant measure\; and (ii) if the noise intensity is small\, the collection of all invariant measures is a non-trivial line segment\, in p articular infinite. Our methods also say a great deal about the structure of these invariant measures. This is based on joint work with Davar Khoshn evisan\, Carl Mueller and Shang-Yuan Shiu.\n LOCATION:https://researchseminars.org/talk/BPS/32/ END:VEVENT BEGIN:VEVENT SUMMARY:Gugan Thoppe (Indian Institute of Science\, Bangalore) DTSTART:20210503T090000Z DTEND:20210503T094500Z DTSTAMP:20260421T141437Z UID:BPS/33 DESCRIPTION:Title: Act ive Cases and Disease Extinction in the Stochastic SIR Model: Estimates wi th Probabilistic Guarantees\nby Gugan Thoppe (Indian Institute of Scie nce\, Bangalore) as part of Bangalore Probability Seminar\n\n\nAbstract\nS IR models\, both deterministic and stochastic\, provide a viable setup for studying epidemics. While the deterministic ones have been around for alm ost a century now\, it hasn't still been possible to obtain analytical est imates for active infections in these setups. Also\, these are not well-su ited to answer questions relating to early termination. The stochastic var iants\, on the other hand\, have indeed been amenable to such analyses. Ho wever\, the current approaches are too complex\; they involve using differ ent approximations (by branching processes\, ODEs\, etc.) for different pa rts of the process.\n\nIn this work\, we consider a discrete-time stochast ic SIR model and take a fundamentally different route to overcome the know n challenges in analyzing SIR models. Namely\, our proofs rely on a sequen ce of stopping times based on jumps in the susceptible population. Their m ain advantage is that the number of recoveries between two successive stop ping times is then a truncated geometric random variable. Our main results include probabilistic bounds for the number of active infections and the disease extinction time. We also obtain an estimate for the expected val ue of the largest epidemic size. This bound matches its analogue in the deterministic case asymptotically. \n\nThis is ongoing work with Dr. Gal Dalal (nVidia\, Israel) and Dr. Balazs Szorenyi (Yahoo Research\, USA).\n LOCATION:https://researchseminars.org/talk/BPS/33/ END:VEVENT BEGIN:VEVENT SUMMARY:Sarath Yasodharan (Indian Institute of Science\, Bangalore) DTSTART:20210503T100000Z DTEND:20210503T104500Z DTSTAMP:20260421T141437Z UID:BPS/34 DESCRIPTION:Title: Lar ge deviations of mean-field interacting particle systems in a fast varying environment\nby Sarath Yasodharan (Indian Institute of Science\, Bang alore) as part of Bangalore Probability Seminar\n\n\nAbstract\nWe consider a weakly interacting Markovian mean-field particle system in a fast varyi ng environment. The particles evolve in the slow time scale and the enviro nment process evolves in the fast time scale. The system is ``fully couple d”\, i.e.\, the evolution of the particles depend on the state of the en vironment\, and the environment itself changes its state depending on the empirical measure of the system of particles. For this two time scale mean -field model\, we prove a process-level large deviation principle for the joint law of the empirical measure process of the particles and the occupa tion measure process of the fast environment. This extends previous result s known for two time scale diffusions to two time scale mean-field models with jumps. Our proof is based on the method of stochastic exponentials. W e characterise the rate function by studying a certain variational problem associated with an exponential martingale.\n\nThis talk is based on joint work with Rajesh Sundaresan.\n LOCATION:https://researchseminars.org/talk/BPS/34/ END:VEVENT BEGIN:VEVENT SUMMARY:Sayantan Chakraborty (TIFR\, Mumbai) DTSTART:20210906T090000Z DTEND:20210906T110000Z DTSTAMP:20260421T141437Z UID:BPS/35 DESCRIPTION:Title: Imp roved Bounds for Perfect Sampling of k-Colorings in Graphs.\nby Sayant an Chakraborty (TIFR\, Mumbai) as part of Bangalore Probability Seminar\n\ n\nAbstract\nI this talk we will present a randomized algorithm that takes as input an undirected n-vertex graph G with maximum degree Δ and an int eger k>3Δ\, and returns a random proper k-coloring of G. The distribution of the coloring is \\emph{perfectly} uniform over the set of all proper k -colorings\; the expected running time of the algorithm is poly(k\,n)=O(n Δ^2⋅log(k)). This improves upon a result of Huber~(STOC 1998) who obtai ned a polynomial time perfect sampling algorithm for k>Δ^2+2Δ. Prior to our work\, no algorithm with expected running time poly(k\,n) was known to guarantee perfectly sampling with sub-quadratic number of colors in gener al. Our algorithm (like several other perfect sampling algorithms includin g Huber's) is based on the Coupling from the Past method. Inspired by the \\emph{bounding chain} approach\, pioneered independently by Huber~(STOC 1 998) and Häggström & Nelander~(Scand. J. Statist.\, 1999)\, we employ a novel bounding chain to derive our result for the graph coloring problem.\ n LOCATION:https://researchseminars.org/talk/BPS/35/ END:VEVENT BEGIN:VEVENT SUMMARY:Sarah Penington (Univ. Bath\, U. K.) DTSTART:20211018T090000Z DTEND:20211018T110000Z DTSTAMP:20260421T141437Z UID:BPS/36 DESCRIPTION:Title: Gen ealogy of the N-particle branching random walk with polynomial tails\n by Sarah Penington (Univ. Bath\, U. K.) as part of Bangalore Probability S eminar\n\n\nAbstract\nThe N-particle branching random walk is a discrete t ime branching particle system with selection consisting of N particles loc ated on the real line. At every time step\, each particle is replaced by t wo offspring\, and each offspring particle makes a jump from its parent's location\, independently from the other jumps\, according to a given jump distribution. Then only the N rightmost particles survive\; the other part icles are removed from the system to keep the population size constant.\nI will discuss recent results and open conjectures about the long-term beha viour of this particle system when N\, the number of particles\, is large. In the case where the jump distribution has regularly varying tails\, bui lding on earlier work of J. Bérard and P. Maillard\, we prove that at a t ypical large time the genealogy of the population is given by a star-shape d coalescent\, and that almost the whole population is near the leftmost p article on the relevant space scale.\n\nBased on joint work with Matt Robe rts and Zsófia Talyigás.\n LOCATION:https://researchseminars.org/talk/BPS/36/ END:VEVENT BEGIN:VEVENT SUMMARY:Riddhipratim Basu (ICTS\, Bengaluru) DTSTART:20211108T090000Z DTEND:20211108T094500Z DTSTAMP:20260421T141437Z UID:BPS/37 DESCRIPTION:Title: A n on-technical introduction to the Liouville quantum gravity metric\nby Riddhipratim Basu (ICTS\, Bengaluru) as part of Bangalore Probability Sem inar\n\n\nAbstract\nInformally speaking\, the Liouville quantum gravity (L QG) metric is a random Riemannian metric on the complex plane given by the metric tensor $\\exp(2\\xi h) (dx^2+dy^2)$ where \\xi is a parameter and h is an appropriate version of the Gaussian free field on $\\mathbb{C}$. I n this talk\, we shall recall basic definitions and review some of the rec ent developments on the construction of this metric and understanding of i ts basic properties. I shall ignore most technical aspects and focus on ge ometric results that are particularly interesting from a first passage per colation perspective.\n LOCATION:https://researchseminars.org/talk/BPS/37/ END:VEVENT BEGIN:VEVENT SUMMARY:Balazs Rath (Budapest University of Technology\, Hungary) DTSTART:20211004T090000Z DTEND:20211004T094500Z DTSTAMP:20260421T141437Z UID:BPS/38 DESCRIPTION:Title: Per colation of worms-I\nby Balazs Rath (Budapest University of Technology \, Hungary) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/38/ END:VEVENT BEGIN:VEVENT SUMMARY:Sándor Rokob (Budapest University of Technology\, Hungary) DTSTART:20211004T100000Z DTEND:20211004T104500Z DTSTAMP:20260421T141437Z UID:BPS/39 DESCRIPTION:Title: Per colation of worms-II\nby Sándor Rokob (Budapest University of Technol ogy\, Hungary) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/39/ END:VEVENT BEGIN:VEVENT SUMMARY:Sumit Mukerjee (Columbia University) DTSTART:20211122T090000Z DTEND:20211122T110000Z DTSTAMP:20260421T141437Z UID:BPS/40 DESCRIPTION:by Sumit Mukerjee (Columbia University) as part of Bangalore P robability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/40/ END:VEVENT BEGIN:VEVENT SUMMARY:Riddhipratim Basu (ICTS\, Bengaluru) DTSTART:20211108T100000Z DTEND:20211108T104500Z DTSTAMP:20260421T141437Z UID:BPS/41 DESCRIPTION:Title: Env ironment seen from infinite geodesics in Liouville quantum gravity\nby Riddhipratim Basu (ICTS\, Bengaluru) as part of Bangalore Probability Se minar\n\n\nAbstract\nIn this second part\, I shall talk about a recent res ult (joint work with Manan Bhatia and Shirshendu Ganguly) on environments seen from infinite geodesics in the LQG metric. The question whether the u nderlying noise seen from an appropriately chosen random point on an infin ite geodesic originated in the context of planar first and last passage pe rcolation models. We shall briefly review some recent progress in those mo dels before turning our attention to a natural formulation of the question in the context of LQG. We shall discuss results establishing the existenc e of a limiting environment and describing some basic properties of the li miting environment.\n LOCATION:https://researchseminars.org/talk/BPS/41/ END:VEVENT BEGIN:VEVENT SUMMARY:Elena Pulvirenti (TU Delft\, Netherlands) DTSTART:20211206T090000Z DTEND:20211206T094500Z DTSTAMP:20260421T141437Z UID:BPS/42 DESCRIPTION:Title: Met astability for the dilute Curie-Weiss model with Glauber dynamics\nby Elena Pulvirenti (TU Delft\, Netherlands) as part of Bangalore Probability Seminar\n\n\nAbstract\nSystems subject to a random dynamics exhibit metas tability when they persist for a very long time in a phase (called metasta ble state) that is different from the one corresponding to the thermodynam ic equilibrium (called stable state). \n\nIn this talk I will analyse the metastable behaviour of the dilute Curie–Weiss model\, a classical model of a disordered ferromagnet\, subject to a Glauber dynamics. The equilibr ium model is a random version of a mean-field Ising model\, where the coup ling coefficients are replaced by i.i.d. random coefficients\, e.g. Bernou lli random variables with fixed parameter p. This model can be also viewed as an Ising model on the Erdos–Renyi random graph with edge probability p.\n\nUnder the Glauber dynamics the system is a Markov chain where spins flip according to a Metropolis dynamics at inverse temperature \\beta. \n \nI will show how to compute the average time the system takes to reach th e stable phase when it starts from a certain probability distribution on t he metastable state (called the last-exit biased distribution)\, in the re gime where the system size goes to infinity\, \\beta is larger than 1 and the magnetic field is positive and small enough. I will explain how to obt ain asymptotic bounds on the probability of the event that the mean metast able hitting time is approximated by that of the Curie–Weiss model.\n\nT he proof uses the potential theoretic approach to metastability and concen tration\n\nof measure inequalities. This is a joint collaboration with Ant on Bovier (Bonn) and \n\nSaeda Marello (Bonn).\n LOCATION:https://researchseminars.org/talk/BPS/42/ END:VEVENT BEGIN:VEVENT SUMMARY:Saeda Marello (Univ. Bonn\, Germany) DTSTART:20211206T100000Z DTEND:20211206T104500Z DTSTAMP:20260421T141437Z UID:BPS/43 DESCRIPTION:Title: Met astability for the Curie-Weiss model on inhomogeneous random graphs: resul ts and challenges\nby Saeda Marello (Univ. Bonn\, Germany) as part of Bangalore Probability Seminar\n\n\nAbstract\nWe are currently trying to ex tend to inhomogeneous random graphs the results on metastability for the C urie-Weiss model (CW) on the Erdős–Rényi random graph (namely the rand omly dilute CW)\, obtained by Anton Bovier\, Elena Pulvirenti and myself\, and presented in the previous talk.\n\nThe idea is the same: obtaining in formation on a target model in terms of the correspondent “mean model” quantities.\n\nAfter presenting few general results\, we will focus on a particular case: the CW on the Chung-Lu inhomogeneous random graph and “ its mean model”\, the so called “CW with disorder”. The latter model will be the core of the talk: we will present results\, techniques and co mparison with known models. This will allow us to see why many details can be obtained there and to point of the challenges we face in other models. \n\nWe use extensively the potential-theoretic approach to metastability.\ n\nBased on ongoing joint work with Anton Bovier and Frank den Hollander.\ n LOCATION:https://researchseminars.org/talk/BPS/43/ END:VEVENT BEGIN:VEVENT SUMMARY:Domenico Marinucci (University of Rome “Tor Vergata”\, Italy) DTSTART:20220124T090000Z DTEND:20220124T094500Z DTSTAMP:20260421T141437Z UID:BPS/44 DESCRIPTION:by Domenico Marinucci (University of Rome “Tor Vergata”\, Italy) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/44/ END:VEVENT BEGIN:VEVENT SUMMARY:Maurizia Rossi (University of Milano-Bicocca\, Italy) DTSTART:20220124T100000Z DTEND:20220124T104500Z DTSTAMP:20260421T141437Z UID:BPS/45 DESCRIPTION:by Maurizia Rossi (University of Milano-Bicocca\, Italy) as pa rt of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/45/ END:VEVENT BEGIN:VEVENT SUMMARY:Alison Etheridge (University of Oxford\, U. K.) DTSTART:20220314T090000Z DTEND:20220314T110000Z DTSTAMP:20260421T141437Z UID:BPS/46 DESCRIPTION:by Alison Etheridge (University of Oxford\, U. K.) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/46/ END:VEVENT BEGIN:VEVENT SUMMARY:Alison Etheridge (University of Oxford\, U. K.) DTSTART:20220316T090000Z DTEND:20220316T110000Z DTSTAMP:20260421T141437Z UID:BPS/47 DESCRIPTION:by Alison Etheridge (University of Oxford\, U. K.) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/47/ END:VEVENT BEGIN:VEVENT SUMMARY:Soumendu Sunder Mukherjee (Indian Statistical Institute\, Kolkata) DTSTART:20220207T090000Z DTEND:20220207T094500Z DTSTAMP:20260421T141437Z UID:BPS/48 DESCRIPTION:by Soumendu Sunder Mukherjee (Indian Statistical Institute\, K olkata) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/48/ END:VEVENT BEGIN:VEVENT SUMMARY:Eliran Subag (Weizmann Institute of Science) DTSTART:20220221T090000Z DTEND:20220221T110000Z DTSTAMP:20260421T141437Z UID:BPS/49 DESCRIPTION:Title: The free energy of pure spherical models: computation from the TAP approach\nby Eliran Subag (Weizmann Institute of Science) as part of Bangalore P robability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/49/ END:VEVENT BEGIN:VEVENT SUMMARY:Kesav Krishnan (Univ. Illinois Urbana-Champaign) DTSTART:20220207T100000Z DTEND:20220207T104500Z DTSTAMP:20260421T141437Z UID:BPS/50 DESCRIPTION:Title: Dis ordered Monomer Dimer Models on Cylinder Graphs\nby Kesav Krishnan (Un iv. Illinois Urbana-Champaign) as part of Bangalore Probability Seminar\n\ nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/50/ END:VEVENT BEGIN:VEVENT SUMMARY:Antti Knowles (University of Geneva) DTSTART:20220411T090000Z DTEND:20220411T110000Z DTSTAMP:20260421T141437Z UID:BPS/51 DESCRIPTION:Title: Spe ctral phases of Erdös-Rényi graphs\nby Antti Knowles (University of Geneva) as part of Bangalore Probability Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/51/ END:VEVENT BEGIN:VEVENT SUMMARY:Ph.D. Students / Postdocs DTSTART:20220425T090000Z DTEND:20220425T110000Z DTSTAMP:20260421T141437Z UID:BPS/52 DESCRIPTION:Title: Sho rt-talks\nby Ph.D. Students / Postdocs as part of Bangalore Probabilit y Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/52/ END:VEVENT BEGIN:VEVENT SUMMARY:Ph.D. Students / Postdocs DTSTART:20220502T090000Z DTEND:20220502T110000Z DTSTAMP:20260421T141437Z UID:BPS/53 DESCRIPTION:Title: Sho rt-talks\nby Ph.D. Students / Postdocs as part of Bangalore Probabilit y Seminar\n\nAbstract: TBA\n LOCATION:https://researchseminars.org/talk/BPS/53/ END:VEVENT END:VCALENDAR