One World Stochastic Numerics and Inverse Problems

From April 2020 to March 2022, the seminar has been supported by ICMS, the International Center for Mathematical Sciences. The seminar series is active. Do not hesitate to contact the organisers for information.

Recorded of some of the older talks are available here.

Organization committee

Charles-Edouard Bréhier, CNRS & Université Lyon 1
Evelyn Buckwar, Linz University
Erika Hausenblas, Loeben University
Ray Kawai, Tokyo University
Gabriel Lord, Radboud University
Michael Tretyakov, Nottingham University
Kostas Zygalakis, University of Edinburgh

Spring/summer 2023 talks:

·         26 April 2023 1pm UK Xu Wang (Chinese Academy of Sciences, Beijing)
Inverse random scattering problems for stochastic wave equations. Recording

·         10 May 2023 1pm UK Chaman Kumar (IIT Roorkee)
Well-posedness and tamed scheme for McKean-Vlasov SDEs Recording

·         24 May 2023 1pm UK Elisabeth Ullmann (Technical University of Munich)
Particle dynamics for rare event estimation with PDE-based models Abstract.

·         7 June 2023 1pm UK Goncalo Dos Reis (University of Edinburgh)
High order splitting methods for stochastic differential equations

·         21 June 2023 4pm UK Nathan Glatt-Holtz (Tulane University, US)


Previous talks

·    22 March 2023 Antoine Tambue (Western Norway University of Applied Sciences)
Magnus-type integrator for the finite element discretization of semilinear parabolic non-autonomous SPDEs driven by multiplicative noise. Recording

·    8 March 2023 Christian Bayer (WIAS, Berlin)
Optimal stopping with signatures Recording

·    8 February 2023 Caroline Bauzet (CNRS, Marseille)
Convergence of monotone finite volume schemes for hyperbolic scalar conservation laws with a multiplicative stochastic force. Abstract. Recording

·    25 January 2023 Savvas Melidonis (Heriot-Watt University)
SDE-based MCMC methods for low-photon imaging inverse problems
Matei Hanu (University of Mannheim)
Subsampling in Ensemble Kalman Inversion

·    14 December 2022 Yubin Yan (University of Chester)
Galerkin finite element approximation of a stochastic semilinear fractional subdiffusion with fractionally integrated additive noise

·    30 November 2022 Rob Scheichl (University of Heidelberg)
 Efficient Rare Event Estimation in High Dimensions

·    16 November 2022 Ben Leimkuhler (University of Edinburgh)
Constrained dynamics algorithms for molecular modelling and statistical computation

·    22 June 2022: Anne Kvaerno (Norwegian University of Science and Technology)
 Stochastic B–series and order conditions for exponential integrators

·    8 June 2022: Claudia Schillings (Freie Universitat Berlin)
A General Framework for Machine Learning based Optimization Under Uncertainty

·    25 May 2022: Michaela Szölgyenyi (University of Klagenfurt)
Stochastic differential equations with irregular coefficients: mind the gap!

·    11 May 2022: Yue Wu (University of Strathclyde)
The numerical approximations for the random periodic solution of S(P)DEs Recording .

·    27 April 2022: Andreas Petersson (University of Oslo)
Numerical approximation of the heat modulated infinite dimensional Heston model Recording .

·    30 March 2022: Gilles Vilmart (Université de Genève)
Superconvergent methods inspired by the Crank-Nicolson scheme in the context of diffusion PDEs

·    16 March 2022: Alain Durmus (ENS Paris-Saclay)
On the geometric convergence for MALA under verifiable conditions

·    02 March 2022: Kristin Kirchner (TU Delft)
When are linear predictions of random fields using wrong mean and covariance functions asymptotically optimal?

·    16 February 2022: Sebastian Reich (University of Potsdam)
The ensemble Kalman filter and its extension to nonlinear and multi-scale filtering problems

·    2 February 2022: Lukasz Szpruch (University of Edinburgh)
From the theory of (stochastic) control to deep learning and back

·    19 January 2022: Annie Millet (Université Paris 1 Panthéon Sorbonne)
Space-time discretization schemes for the 2D Navier Stokes equations with additive noise

·    15 December 2021: Toshihiro Yamada (Hitotsubashi University)
Deep learning and probabilistic methods for solving high-dimensional linear/nonlinear parabolic PDEs

·    1 December 2021: Aretha Teckentrup (University of Edinburgh)
Convergence, Robustness and Flexibility of Gaussian Process Regression

·    17 November 2021: Irene Tubikanec (Johannes Kepler University, Linz)
Splitting methods for SDEs with locally Lipschitz drift. An illustration on the FitzHugh-Nagumo model

·    3 November 2021: Arturo Kohatsu-Higa (Ritsumeikan University)
Simulation of Reflected Brownian motion on two dimensional wedges

·    20 October 2021: Emmanuel Gobet (Ecole Polytechnique)
How to generate the path of Fractional Brownian motion with a ReLU-Neural Networks

·    6 October 2021: Tony Shardlow (University of Bath)
Contaminant dispersal, numerical simulation, and stochastic PDEs

·    22 September 2021: Raul Tempone (KAUST)
Combining Hierarchical Approximation with Importance Sampling: Approximation and Optimization techniques

·    7 July 2021: Gabriel Stoltz (Ecole des Ponts and Inria Paris)
Computation of transport coefficients in molecular dynamics: methods and numerical analysis

·    23 June 2021: Annika Lang (Chalmers University)
Connecting random fields on manifolds and stochastic partial differential equations in simulations

·    9 June 2021: Laura Scarabosio (Radboud University)
Shape uncertainty quantification for non-smooth quantities of interest

·    26 May 2021: Erika Hausenblas (Montanuniversitaet Leoben)
Stochastic Activator-Inhibitor models and its Numerical Modelling

·    31 March 2021: Monika Eisenmann (Lund University)
Sub-linear convergence of stochastic optimization methods in Hilbert space

·    17 March 2021: Konstantinos Dareiotis (University of Leeds)
Approximation of stochastic equations with irregular drifts

·    3 March 2021: Andrew Stuart (Caltech)
Inverse Problems Without Adjoints

·    17 February 2021: Svetlana Dubinkina (Vrije Universiteit Amsterdam)
Shadowing approach to data assimilation

·    3 February 2021: Denis Talay (Inria and Ecole Polytechnique)
Probability distributions of first hitting times of solutions to SDEs w.r.t. the Hurst parameter of the driving fractional Brownian noise: A sensitivity analysis

·    16 December 2020: Evelyn Buckwar (Johannes Kepler University, Linz)
A couple of ideas on splitting methods for SDEs

·    2 December 2020: Andreas Prohl (Tübingen)
Numerical methods for stochastic Navier-Stokes equations

·    18 November 2020: Sonja Cox (Amsterdam)
Efficient simulation of generalized Whittle-Matérn fields

·    4 November 2020: Marta Sanz-Solé (Barcelona)
Global existence for stochastic waves with super-linear coefficients

·    21 October 2020: Mireille Bossy (Inria)
SDEs with boundaries, modelling particle dynamics in turbulent flow

·    7 October 2020: Raphael Kruse (Halle-Wittenberg)
On the BDF2-Maruyama method for stochastic evolution equations

·    23 September 2020: Adrien Laurent (University of Geneva)
Order conditions for sampling the invariant measure of ergodic stochastic differential equations in R^d and on manifolds

·    9 October 2020: Chuchu Chen (Chinese Academy of Sciences)
Probabilistic superiority of stochastic symplectic methods via large deviations principle

·    8 July 2020: Georg Gottwald (University of Sydney)
Simulation of non-Lipschitz stochastic differential equations driven by α-stable noise: a method based on deterministic homogenisation

·    1 July 2020: Akash Sharma & Michael Tretyakov (University of Nottingham)
Computing ergodic limits of reflected diffusions and sampling from distributions with compact support

·    24 June 2020: Kody Law (University of Manchester)
Bayesian Static Parameter Estimation using Multilevel and multi-index Monte Carlo

·    17 June 2020: Ray Kawai (University of Tokyo)
Stochastic approximation in adaptive Monte Carlo variance reduction

·    10 June 2020: Marco Iglesias (University of Nottingham)
Ensemble Kalman Inversion: from subsurface environments to composite materials

·    3 June 2020: Gabriel Lord (Radboud University)
Numerics and SDE a model for the stochastically forced vorticity equation

·    27 May 2020: David Cohen (Umea University)
Drift-preserving schemes for stochastic Hamiltonian and Poisson systems

·    20 May 2020: Abdul Lateef Haji-Ali (Heriot Watt University)
Sub-sampling and other considerations for efficient risk estimation in large portfolios

·    6 May 2020: Conall Kelly (University College Cork)
A hybrid, adaptive numerical method for the Cox-Ingersoll-Ross model

·    29 April 2020: Charles-Edouard Bréhier ( CNRS & Université Lyon 1)
Analysis of splitting schemes for the stochastic Allen-Cahn equation

·    22 April 2020: Xuerong Mao (Strathclyde)
The Truncated Euler-Maruyama Method for Stochastic Differential Delay Equations

·    15 April 2020: Kostas Zygalakis (University of Edinburgh)
Explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems