

Last update: June 21th
Minisymposium title  session #  Speaker's Name  Talk Title  
On the power of iid information for (nonlinear) approximation organised by Mathias Sonnleitner and Mario Ullrich 
session 1  Mario Ullrich  On recent advances in approximation based on iid data  
Matthieu Dolbeault  Approximation with iid, reduced, or greedy sampling strategies  
Albert Cohen  Nonlinear approximation spaces for inverse problems  
Sebastian Moraga  Optimal learning of infinitedimensional holomorphic functions from i.i.d. samples  
session 2  Art Owen  Mean Dimension of Radial Basis Functions  
Robert J. Kunsch  Uniform Approximation of Finite Sequences with Randomized Algorithms  
Fabian Taubert  DimensionIncremental Function Approximation Using MonteCarlo Methods  
Numerics for SPDEs organised by Charles Edouard Bréhier 
session 1  Guillaume Dujardin  Numerical methods for the nonlinear stochastic Manakov system  
Ludovic Goudenège  Tamed Euler scheme for SPDE with distributional drift  
Gabriel Lord  Adaptive/Tamed methods for SPDEs with additive noise  
Kerstin Schmitz  Convergence of a finitevolume scheme for a stochastic heat equation with a multiplicative Lipschitz noise  
PDMP and related topics organised by Daniel Paulin 
session 1  George Deligiannidis  NonReversible Parallel Tempering: a Scalable Highly Parallel MCMC Scheme  
Kengo Kamatani  Scaling of Piecewise Deterministic Monte Carlo for Anisotropic Targets  
Augustin Chevallier  Adaptive Metropolized PDMP sampling using the NoUTurn criterion  
Sebastiano Grazzi  PDMP samplers with boundary conditions  
Recent advances in MCM for forward and inverse problems for stochastic reaction networks organised by Chiheb Ben Hammouda, Nadhir Ben Rached and Raul Tempone 
session 1  Sophia Wiechert  Markovian Projection for Efficient Importance Sampling of Stochastic Reaction Networks  
Fang Zhou  A scalable approach for solving chemical master equations based on modularization and filtering  
Ankit Gupta  Frequency domain methods for analysing stochastic reaction networks  
David Warne  Multifidelity multilevel approximate Bayesian computation for stochastic biochemical reaction networks  
Slice sampling and adaptive MCMC organised by Daniel Rudolf 
session 1  Mareike Hasenpflug  Slice Sampling on the Sphere  
Philip Schär  Making Polar Slice Sampling Efficiently Implementable  
Julian Hofstadler  Adaptive MCMC for doubly intractable distributions  
Andi Wang  Comparison theorems for Hybrid Slice Sampling  
Numerical methods in statistical physics organised by Alessandra Iacobucci and Gabriel Stoltz 
session 1  Pierre Monmarché  Quantitative convergence bounds for kinetic Langevin and HMC  
Régis Santet  Unbiasing HMC Algorithms For General Hamiltonian Functions  
Pierre Illien  Brownian dynamics simulations of colloids propelled by mesoscale phase separations  
Pierfrancesco Urbani  Dynamical meanfield theory for stochastic gradient descent in high dimensions  
session 2  Gilles Vilmart  Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations  
Petr Plechac  Estimating linear response and sensitivity analysis of nonequilibrium steady states  
Dominic Phillips  Coordinate Transforms for Efficient Brownian Dynamics Simulations  
Shiva Darshan  Sticky Coupling as a Control Variate for Sensitivity Analysis  
session 3  Juliane U. Klamser  Can Monte Carlo methods be used to simulate activematter systems?  
Noé Blassel  Stochastic Norton Dynamics  
Thomas Pigeon  Adaptive multilevel splitting used to machine learn committor function  
Gideon Simpson  Infinite Dimensional Nonlocal Diffusions with Additive Noise  
session 4  Michela Ottobre  Uniform in time approximations of stochastic dynamics  
Matthew Dobson  SteadyState Solutions for Nonequilibrium Langevin Dynamics  
Renato Spacek  Extending the regime of linear response with synthetic forcings  
Grigorios Pavliotis  On the DiffusiveMean Field Limit for Weakly Interacting Diffusions Exhibiting Phase Transitions  
Variance reduction techniques for rare events organised by Nadhir Ben Rached and Raul Tempone 
session 1  Nadhir Ben Rached  Importance sampling via stochastic optimal control for McKeanVlasov stochastic differential equation  
Shyam Mohan  Multilevel and Multiindex Monte Carlo methods for rare events associated with McKeanVlasov equation  
Bruno Tuffin  Bounds, Assessment and Confidence Intervals for Exponential Approximations  
Charly Andral  The Importance Markov Chain  
session 2  Eya Ben Amar  Statedependent Importance Sampling for Estimating Expectations of Functionals of Sums of Independent Random Variables  
Gerardo Rubino  Estimating network resilience, a performability metric  
Martin Chak  Optimal friction in Langevin dynamics  
Stochastic Computation and Complexity organised by Stefan Heinrich, Thomas MüllerGronbach and Larisa Yaroslavtseva 
session 1  Andreas Neuenkirch  The robustness of the Euler scheme for scalar SDEs with nonLipschitz diffusion coefficients  
Konstantinos Dareiotis  Asymptotic error distribution of the Euler method for stochastic differential equations with irregular drifts  
Verena Schwarz  Randomized Milstein algorithm for approximation of solutions of jumpdiffusion SDEs  
Andre Herzwurm  On upper and lower bounds for strong approximation of scalar SDEs with reflecting boundary  
session 2  Randolf Altmeyer  Approximation of occupation time functionals and related approximations of Ito processes  
Simon Ellinger  Sharp lower error bounds for strong approximation of SDEs with piecewise Lipschitz continuous drift  
Mate Gerenczer  Milstein scheme for SDEs with irregular drift  
Larisa Yaroslavtseva  Sharp lower error bounds for strong approximation of SDEs with a drift coefficient of Sobolev regularity s in (1/2,1)  
session 3  Daniel Rudolf  Convergence and welldefinedness of ellitpical slice sampling  
Tomasz Bochacik  On error bounds, optimality and exceptional sets for selected randomized schemes for ODEs  
Sonja Cox  Infinitedimensional Wishart processes  
Pierre Bras  Convergence of LangevinSimulated Annealing Algorithms with Multiplicative Noise  
session 4  Michaela Szölgyenyi  A higher order approximation method for jumpdiffusion SDEs with discontinuous drift coefficient  
Tim Johnston  Nonasymptotic Bounds for EM via Interacting Particle Systems  
Gunther Leobacher  McKean–Vlasov equations with discontinuous drift  
Oleg Butkovsky  Strong rate of convergence of the Euler scheme for SDEs with irregular drift driven by Levy noise 

session 5  Lukasz Stepien  Adaptive stepsize control for global approximation of SDEs driven by countably dimensional Wiener process  
Monika Eisenmann  Domain decomposition methods for SPDEs  
Sotirios Sabanis  Adaptive stochastic optimizers, EulerKrylov’s polygonal approximations and the training of neural nets  
Stefan Heinrich  Randomized Complexity of VectorValued Approximation  
SDEs: Theory, Numerics and Applications organised by Gabriel Lord 
session 1  Mireille Bossy  Stochastic approach for the simulation of nonspherical particles in turbulence  
Evelyn Buckwar  Construction and analysis of splitting methods for Chemical Langevin Equations  
Khadija Meddouni  Numerical methods for stochastic neural field equations  
Conall Kelly  Adaptive Meshes for Stochastic Jump Differential Equations  
MCM for reactor physics organised by Andrea Zoia and Eric Dumonteil 
session 1  Mathias Rousset  Fluctuations of Rare Event Simulation with Monte Carlo Splitting in the Small Noise Asymptotics  
Davide Mancusi  Variance Reduction and Noise Source Sampling Techniques for Monte Carlo Simulations of Neutron Noise  
Vince Maes  Estimating the statistical error of analog particletracing Monte Carlo methods  
Benjamin Dechenaux  Percolation properties of the neutron population in nuclear reactors  
session 2  Emma Horton  A binary branching model with Morantype interactions  
Elod Pazman  Comparison of Dynamic and Static Flux Estimators and Their Impact on Group Constant Production in the TimeDependent Monte Carlo Reactor Code GUARDYAN  
Alex Cox  Twisted particle filters for neutron transport  
Andrea Zoia  Analysis of heterogeneous Markov media for particle transport problems  
PDMPs for high dimensional sampling: theory and application organised by Ritabrata Dutta and Benedict Leimkuhler 
session 1  Guillaume Chennetier  Adaptive importance sampling based on fault tree analysis for piecewise deterministic Markov process  
Joris Bierkens  A detailed investigation of subsampling regimes for PDMPs  
Matthias Sachs  Posterior Computation with the Gibbs ZigZag Sampler  
Ritabrata Dutta  Exact sampling of scoring rule posterior using Gibbs Boomerang  
session 2  Alexandre BouchardCote  PDMPs as Monte Carlo algorithms models  
Nawaf BouRabee  Randomized Time Integrator for Unadjusted Hamiltonian MCMC  
Peter A. Whalley  Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics  
Torben Sell  GradientBased Markov Chain Monte Carlo for Bayesian Inference With NonDifferentiable Priors  
Monte Carlo Methods for Bayesian inference and optimization organised by Lotfi Chaari 
session 1  Savvas Melidonis  Efficient Bayesian computation for lowphoton imaging problems  
Emilie Chouzenoux  PMCnet for Efficient Bayes Inference in Neural Networks  
Mohamed Fakhfakh  Hamiltonian Monte Carlo Bayesian Optimization for Sparse Neural Networks  
Nadege Polette  Bayesian Inference for Inverse Problems with Hyperparameters Estimation of the Field Covariance Function  
High dimensional integration and approximation organised by Frances Kuo 
session 1  James Nichols  Community detection with entropic regularization  
Alexander Gilbert  Density estimation in uncertainty quantification using quasiMonte Carlo methods with preintegration  
Michael Feischl  A quasiMonte Carlo data compression algorithm for machine learning  
Vesa Kaarnioja  On the Periodic Model of Uncertainty Quantification With Application to Bayesian Inverse Problems  
session 2  Abirami Srikumar  Multilevel quasiMonte Carlo methods for kernel interpolation in uncertainty quantification  
Dirk Nuyens  Higher order lattice rules on Rd  
Yoshihito Kazashi  Density estimation in RKHS with application to Korobov spaces in high dimensions  
Ian Sloan  Periodic kernelbased highdimensional approximation  
Recent Progress in Langevin MC organised by Jun Yang 
session 1  Alain Durmus  On the convergence of the Unadjusted and Metropolis Adjusted Langevin Algorithms  
Tyler Farghly  Adaptive Langevin Monte Carlo methods for heavytailed sampling via weighted functional inequalities  
Sifan Liu  Langevin QuasiMonte Carlo  
Konstantinos Zygalakis  Accelerating MCMC for imaging science by using an implicit Langevin algorithm  
MLMC techniques for discontinuous functionals organised by Chiheb Ben Hammouda and Raul Tempone 
session 1  Chiheb Ben Hammouda  MLMC Combined with Numerical Smoothing for Efficient Probabilities Computation, Density Estimation, and Option Pricing  
AbdulLateef HajiAli  Multilevel Path Branching for Digital Options  
Ahmed Kebaier  The interpolated drift implicit Euler scheme Multilevel Monte Carlo method for pricing Barrier options and applications to the CIR and CEV models  
Andreas Stein  An antithetic multilevel Monte Carlo Milstein scheme for SPDEs  
session 2  Sebastian Krumscheid  Multilevel Monte Carlo methods for parametric expectations: distribution and robustness measures  
Fabio Nobile  MLMC for the computation of CVaR and its sensitivities in PDEconstrained riskaverse optimization  
Cedric Beschle  CLMC techniques for elliptic PDEs with random discontinuities  
Daniel Roth  Multilevel Monte Carlo Learning  
Nonreversible processes: theory and applications organised by Daniel Adams, Goncalo Dos Reis and Hong Duong 
session 1  Giovanni Conforti  A probabilistic view of Sinkhorn’s algorithm  
Arnaud Guillin  Pair of run and tumble processes with interactions: invariant measure, jamming and mixing time  
Carsten Hartmann  Constraints, strong confinement limits and conditional expectations in nonreversible Langevin dynamics  
Daniel T. Adams  The Structure of GENERIC, Hypocoercivity, and Variational Schemes  
Sampling Strategies for Bayesian Inference organised by Elena Akhmatskaya and Jesus Maria SanzSerna 
session 1  Konstantinos Zygalakis  Bayesian Inference with DataDriven Image Priors Encoded by Neural Networks  
Luke Shaw  Rotationbased Integrators for HMC  
Nicola Branchini  Generalized SelfNormalized Importance Sampling  
L. Nagar & M. Parga Pazos  Adaptive Integration Approach for Sampling with Hamiltonian Monte Carlo Based Methods  
Convergence results for kinetic samplers organised by Pierre Monmarché 
session 1  Lionel RiouDurand  Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo  
Katharina Schuh  Convergence of unadjusted Hamiltonian Monte Carlo and Langevin dynamics via couplings  
Lucas Journel  Sampling of singular Gibbs measure  
Lihan Wang  Convergence Rates of Kinetic Sampling Dynamics via Spacetime Poincarétype Inequality  
Exploring the intersections of importance sampling, MCMC, and optimization organised by Dootika Vats 
session 1  Juan Kuntz  ParticleBased Algorithms for Maximum Likelihood Estimation of Latent Variable Models  
Jimmy Olsson  PaRISian particle Gibbs samplers for state and pa rameter learning in nonlinear statespace models  
Víctor Elvira  MCMCdriven adaptive importance samplers  
Dootika Vats  Comparing apples to oranges: a universal effective sample size  
(Quasi)MC Software organised by Fred Hickernell and Pieterjan Robbe 
session 1  Aleksei Sorokin  Collaborative Integrations with the QMCPy Framework  
Anne Reinarz  UMBridge  
Mikkel Lykkegaard  TinyDA: Multilevel Delayed Acceptance MCMC for Human Beings  
Pieterjan Robbe  Multilevel Delayed Acceptance MCMC for the prediction of xenon diffusion in UO2 nuclear fuel  
Sampling Schemes: Quality Measures, Point Generation, and Applications organised by Michael Gnewuch and Florian Pausinger 
session 1  François Clement  Subset Sampling for Low Discrepancy Point Sets  
Jasmin Fiedler  Maximal inequalities in Discrepancy theory  
Nathan Kirk  Stratified Sampling of the Unit Cube  
Zexin Pan  Superpolynomial Accuracy of Medianofmeans  
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