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.
Charles-Edouard
Bréhier, CNRS & Université Lyon 1
Evelyn Buckwar, Linz University
Nathan Glatt-Holtz, Tulane University
Gabriel Lord, Radboud University
Michael
Tretyakov, Nottingham University
Kostas
Zygalakis, University of Edinburgh
· 27 November 2024: 2-3pm Hannes Vandecasteele
(Johns Hopkins University)
A
micro-macro Markov chain Monte Carlo using reaction coordinate proposals with
applications in molecular dynamics Recording
· 05 March 2025: 2-3pm Hakima Bessaih (Florida
International University)
An
overview of numerical schemes for stochastic hydrodynamics Recording
· 19 March 2025: Xiaojie Wang (Central
South University)
·
11 December 2024: 1-2pm Martin Hutzenthaler
(University of Duisburg Essen)
Strong convergence rates for stochastic Burgers equations Recording
·
27 November 2024: 1-2pm James Foster (University
of Bath)
Splitting methods and generative modelling for high order SDE
simulation Recording
·
13 November 2024 Katharina
Johanna Schuh (TU Wien) Recording
Convergence of kinetic Langevin samplers
for non-convex potentials
·
30 October 2024: Giorgos
Vasdekis (Newcastle University)
Skew-symmetric schemes for SDEs and where to
find them Recording
· 19 June 2024: Mike Giles (University of Oxford)
Strong
convergence of path sensitivities Recording
· 05 June 2024: 1-2pm Tony Lelièvre (Ecole des Ponts)
A spectral
approach to the narrow escape problem in the disk Recording
· 08 May 2024 1-2pm UK time: Christoph Reisinger (University of Oxford)
Numerical
approximation of Zakai SPDEs with fast volatility Recording
· 20 March 2024: Nadhir Ben Rached (University of Leeds)
Importance
Sampling for McKean-Vlasov Stochastic Differential
Equation Recording
· 6 March 2024: Diyora Salimova (University of Freiburg)
Deep neural network
approximations for partial differential equations Recording
· 21 February 2024: Ludovic Goudenège (Centrale Supélec)
Regularisation
by noise for stochastic heat equations with nonlinear and distributional drifts
Recording
· 7 February 2024: Neil Chada (Heriot Watt University)
A Dynamic
Variant of Iteratively Regularized Gauss–Newton Method
· 6 December 2023 1pm UK Jianbo Cui (Hong Kong Polytechnic University)
Time Discretizations of Wasserstein-Hamiltonian Flows Recording
·
22 November 2023 1pm UK Helmut
Harbrecht (University of Basel)
Domain uncertainty quantification - modelling
and simulation Recording
·
8 November 2023 2pm UK Lubomir Banas (University of Bielefeld)
Robust a posteriori estimates and adaptivity for the stochastic Cahn-Hilliard equation Recording
·
25 October 2023 1pm UK Xin Tong (National University of Singapore)
Ensemble Kalman
inversion for high dimensional problems Recording
·
11 October 2023 2pm UK Dimitra Antonopoulou (University
of Chester)
Space-time Discontinuous Galerkin
Methods for the epsilon-dependent Stochastic Allen-Cahn Equation with mild
noise 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