Mathematics, Physics and Machine Learning (IST, Lisbon)

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data structures and algorithms machine learning mathematical physics information theory optimization and control data analysis, statistics and probability

Instituto Superior Técnico

Audience: Researchers in the topic
Seminar series time: Thursday 16:00-17:00 in your time zone, UTC
Organizers: Cláudia Nunes, Cláudia Soares, Francisco Melo, João Seixas, João Xavier, Jose Mourao*, Mário Figueiredo, Pedro Alexandre Santos, Yasser Omar
*contact for this listing

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Zoom link: videoconf-colibri.zoom.us/j/91599759679

Upcoming talks
Past talks
Your timeSpeakerTitle
ThuOct 2116:00Constantino TsallisStatistical mechanics for complex systems
ThuOct 1416:00Clément HonglerNeural Tangent Kernel
ThuSep 3016:00Volkan CevherOptimization Challenges in Adversarial Machine Learning
ThuSep 2309:00Leong Chuan KwekMachine Learning and Quantum Technology
ThuSep 1616:00J. Nathan KutzDeep learning for the discovery of parsimonious physics models
WedJul 2816:00Simon DuProvable Representation Learning
FriJul 0913:00Usman KhanDistributed ML: Optimal algorithms for distributed stochastic non-convex optimization
FriJul 0213:00Ard LouisDeep neural networks have an inbuilt Occam's razor
FriJun 2513:00Yuejie ChiPolicy Optimization in Reinforcement Learning: A Tale of Preconditioning and Regularization
FriJun 1813:00Ruth MisenerPartition-based formulations for mixed-integer optimization of trained ReLU neural networks
FriJun 1113:00Ulugbek KamilovComputational Imaging: Reconciling Physical and Learned Models
FriJun 0413:00Mathieu BlondelEfficient and Modular Implicit Differentiation
FriMay 2813:00Gustau Camps-VallsPhysics Aware Machine Learning for the Earth Sciences
FriMay 2113:00Kyriakos VamvoudakisLearning-Based Actuator Placement and Receding Horizon Control for Security against Actuation Attacks
FriMay 0713:00Rebecca WillettMachine Learning and Inverse Problems: Deeper and More Robust
WedApr 2817:00Mikhail BelkinTwo mathematical lessons of deep learning
FriApr 2313:00Jan PetersRobot Learning - Quo Vadis?
WedApr 1417:00Gabriel PeyréScaling Optimal Transport for High dimensional Learning
FriApr 0913:00Pedro A. SantosTwo-time scale stochastic approximation for reinforcement learning with linear function approximation
WedMar 3117:00Steve BruntonMachine learning for Fluid Mechanics
MonMar 2217:00Markus HeylQuantum many-body dynamics in two dimensions with artificial neural networks
WedMar 1718:00Hsin Yuan Huang, (Robert)Information-theoretic bounds on quantum advantage in machine learning
WedMar 0318:00A. Pedro AguiarModel based control design combining Lyapunov and optimization tools: Examples in the area of motion control of autonomous robotic vehicles
MonFeb 2217:00Maciej Koch-J8anuszStatistical physics through the lens of real-space mutual information
WedFeb 1718:00Mário FigueiredoDealing with Correlated Variables in Supervised Learning
WedFeb 1018:00Caroline UhlerCausal Inference and Overparameterized Autoencoders in the Light of Drug Repurposing for SARS-CoV-2
WedFeb 0318:00Miguel CouceiroMaking ML Models fairer through explanations, feature dropout, and aggregation
WedJan 2711:00Xavier BressonBenchmarking Graph Neural Networks
WedJan 2018:00James HalversonNeural Networks and Quantum Field Theory
WedJan 1318:00Anna C. GilbertMetric representations: Algorithms and Geometry
WedJan 0618:00Sanjeev AroraThe quest for mathematical understanding of deep learning
WedDec 1618:00René VidalFrom Optimization Algorithms to Dynamical Systems and Back
WedDec 0918:00Samantha KleinbergData, Decisions, and You: Making Causality Useful and Usable in a Complex World
WedDec 0218:00Gitta KutyniokDeep Learning meets Physics: Taking the Best out of Both Worlds in Imaging Science
WedNov 2518:00Tommaso DorigoDealing with Systematic Uncertainties in HEP Analysis with Machine Learning Methods
FriNov 2015:00Carola-Bibiane SchönliebCombining knowledge and data driven methods for solving inverse imaging problems - getting the best from both worlds
WedNov 1111:00Bin DongLearning and Learning to Solve PDEs
WedNov 0418:00Joan BrunaMathematical aspects of neural network learning through measure dynamics
WedOct 2818:00Florent KrzakalaSome exactly solvable models for statistical machine learning
WedOct 2117:00Mauro MaggioniLearning Interaction laws in particle- and agent-based systems
WedOct 1417:00Lindsey GrayGraph Neural Networks for Pattern Recognition in Particle Physics
WedOct 0710:00Weinan EMachine Learning and Scientific Computing
WedSep 3017:00Gunnar CarlssonTopological Data Analysis and Deep Learning
ThuJul 3016:30Masoud MohseniTensorFlow Quantum: An open source framework for hybrid quantum-classical machine learning.
ThuJul 2316:30Marylou GabriéProgress and hurdles in the statistical mechanics of deep learning
ThuJul 1616:30João Miranda LemosReinforcement learning and adaptive control
ThuJul 0916:30Francisco C. SantosClimate action and cooperation dynamics under uncertainty
ThuJul 0216:30Kyle CranmerOn the Interplay between Physics and Deep Learning.
ThuJun 2516:30Csaba SzepesváriConfident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting
ThuJun 1816:30João XavierLearning from distributed datasets: an introduction with two examples
ThuJun 1116:30Marcelo PereyraEfficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau
ThuJun 0416:30Afonso BandeiraComputation, statistics, and optimization of random functions
ThuMay 2816:30Hilbert Johan KappenPath integral control theory
ThuMay 2116:30André David MendesHow we discovered the Higgs ahead of schedule - ML's role in unveiling the keystone of elementary particle physics
ThuMay 1416:30Cláudia SoaresThe learning machine and beyond: a tour for the curious
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