Oxford Stochastic Analysis and Mathematical Finance Seminar

analysis of PDEs probability

Audience:	Researchers in the topic
Seminar series time:	Monday 15:00-16:00 in your time zone, UTC
Organizers:	Rama Cont*, Terry Lyons
	*contact for this listing

Description: Probability, stochastic analysis and mathematical finance

Please register through the link provided in the Google calendar and you will receive a livestream link and password for participation:

calendar.google.com/calendar/embed?src=heqabu0gncg8vnurcpb23mfc1k%40group.calendar.google.com&ctz=Europe%2FLondon

Upcoming talks

Past talks

Your time			Speaker	Title
Mon	Oct 25	15:00	Isao Sauzedde	Brownian windings
Mon	Nov 01	16:00	Yvain Bruned	Locality for singular stochastic PDEs
Mon	Nov 08	16:00	David Proemel	Model-free portfolio theory: a rough path approach

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Your time			Speaker	Title
Mon	Oct 18	15:00	Gregorios Pavliotis	On the diffusive-mean field limit for weakly interacting diffusions exhibiting phase transitions
Mon	Oct 11	15:00	Samuel Cohen	Arbitrage-free market models via neural SDEs
Mon	Jun 21	15:00	Jin Ma	Set-valued Backward SDEs and Set-valued Stochastic Analysis
Mon	Jun 14	15:00	Jean-Pierre Fouque	Linear-Quadratic Stochastic Differential Games on Directed Chain Networks
Mon	Jun 07	15:00	Yuchong Zhang	Risk-Taking Contest and its Mean Field Approximation
Mon	May 24	15:00	Davar Khoshnevisan	Phase Analysis for a family of stochastic reaction-diffusion equations
Mon	May 17	15:00	Fraydoun Rezakhanlou	Kinetic Theory for Hamilton-Jacobi PDEs
Mon	May 10	15:00	Ilya Chevyrev	Superdiffusive limits for deterministic fast-slow dynamical systems
Mon	Apr 26	15:00	Thaleia Zariphopoulou	Human-machine interaction models and robo-advising
Mon	Mar 15	16:00	Bruno Bouchard	Ito formula for C1 functionals and path-dependent applications in mathematical finance
Mon	Mar 08	16:00	Pierre Del Moral	A backward Ito-Ventzell formula with an application to stochastic interpolation
Mon	Mar 01	16:00	‪Michael Röckner	Nonlinear Fokker-Planck equations with measures as initial data and McKean-Vlasov equations
Mon	Feb 22	16:00	Benjamin Fehrman	Non equilibrium fluctuations in interactive particle systems and conservative Stochastic PDEs
Mon	Feb 15	16:00	Stefano Olla	Thermal boundaries for energy superdiffusion
Mon	Feb 08	16:00	Martin Larsson	Finance and Statistics: Trading Analogies for Sequential Learning
Mon	Feb 01	16:00	Titus Lupu	Extremal distance and conformal radius of a $CLE_4$ loop.
Mon	Jan 25	16:00	Donghan Kim	Open Markets
Mon	Jan 18	16:00	Mathieu Lauriere	Machine Learning for Mean Field Games
Mon	Dec 07	16:00	Patrick Cheridito	Efficient approximation of high-dimensional functions with neural networks
Mon	Nov 30	16:00	Beatrice Acciaio	Model-independence in a fixed-income market and weak optimal transport
Mon	Nov 23	16:00	RenYuan Xu	Excursion risk
Mon	Nov 16	16:00	Massimiliano Gubinelli	Elliptic stochastic quantisation and supersymmetry
Mon	Nov 09	16:00	Diyora Salimova	Space-time deep neural network approximations for high-dimensional partial differential equations
Mon	Nov 02	16:00	Julien Dubedat	Stochastic Ricci Flow on surfaces
Mon	Oct 26	16:00	Steve Shreve	Diffusion Limit of Poisson Limit-Order Book Models
Mon	Oct 19	15:00	Christa Cuchiero	Deep neural networks, generic universal interpolation and controlled ODEs
Mon	Oct 12	15:00	Ioannis Karatzas	A trajectorial approach to the gradient flow properties of conservative diffusions and Markov chains
Mon	Jun 22	15:00	Thomas Kurtz	Controlled and constrained martingale problems
Mon	Jun 15	15:00	Mykhaylo Shkolnikov	Local stochastic volatility and the inverse of the Markovian projection
Mon	Jun 08	15:00	Christina Goldschmidt	The scaling limit of a critical random directed graph
Mon	Jun 01	15:00	Frederi Viens	A martingale approach for fractional Brownian motions and related path dependent PDEs
Mon	May 25	15:00	Fabian Harang	Infinitely regularising paths and regularisation by noise.
Mon	May 18	15:00	Ivan Nourdin	The functional Breuer-Major theorem
Mon	May 11	15:00	Alexander Schied	Weierstrass bridges
Mon	May 04	15:00	Xin Guo	Connecting Generative adversarial networks with Mean Field Games

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