Day by day Program

The book of abstracts is available here.

Day by day program: MS & CT (last update June 21th)

Monday 26    
10h45 Mini-symposia    
Stochastic Computation and Complexity 1
Amphi 25
Andreas Neuenkirch The robustness of the Euler scheme for scalar SDEs with non-Lipschitz 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 jump-diffusion SDEs
Andre Herzwurm On upper and lower bounds for strong approximation of scalar SDEs with reflecting boundary
On the power of iid information for (non-linear) approximation 1
24-25 S. 101
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 infinite-dimensional holomorphic functions from i.i.d. samples
Numerics for SPDEs
15-25 S. 102
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 finite-volume scheme for a stochastic heat equation with a multiplicative Lipschitz noise
PDMP and related topics
15-25 S.104
George Deligiannidis Non-Reversible 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 No-U-Turn criterion
Sebastiano Grazzi PDMP samplers with boundary conditions
14h30 Mini-symposia & Contributed talks    
Numerical methods in statistical physics 1
Amphi 25
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 mean-field theory for stochastic gradient descent in high dimensions
Variance reduction techniques for rare events 1
24-25 S. 101
Nadhir Ben Rached Importance sampling via stochastic optimal control for McKean-Vlasov stochastic differential equation
Shyam Mohan Multilevel and Multi-index Monte Carlo methods for rare events associated with McKean-Vlasov equation
Bruno Tuffin Bounds, Assessment and Confidence Intervals for Exponential Approximations
Charly Andral The Importance Markov Chain
Slice sampling and adaptive MCMC
15-25 S. 102
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
Contributed talks 1
15-25 S.104
Noufel Frikha On the convergence of the Euler-Maruyama scheme for McKean-Vlasov SDEs
Goncalo Dos Reis High order splitting methods for stochastic differential equations
Wei Cai An Iterative Probabilistic Method for Mixed Problems Of Laplace Equations with the Feynman--Kac Formula of Killed Brownian Motions
Stefano Pagliarani Numerical approximation of McKean-Vlasov SDEs via Stochastic Gradient Descent
Tuesday 27    
10h30 Mini-symposia & Contributed talks    
Numerical methods in statistical physics 2
Amphi 25
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 non-equilibrium steady states
Dominic Phillips Coordinate Transforms for Efficient Brownian Dynamics Simulations
Shiva Darshan Sticky Coupling as a Control Variate for Sensitivity Analysis
SDEs theory and applications
24-25 S. 101
Mireille Bossy Stochastic approach for the simulation of non-spherical 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
Recent advances in MCM for forward and inverse problems for stochastic reaction networks
15-25 S. 102
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
Contributed talks 2
15-25 S.104
Till Massing Simulating Continuous-Time Autoregressive Moving Average Processes Driven By Tempered Stable Lévy Processes
Wei Xu Random Willow Tree with Application in Risk Management
Jonathan Spence Efficient Risk Estimation for the Credit Valuation Adjustment
Raaz Dwivedi Compress then test: Powerful Kernel Testing in Near-linear Time
12h30 Poster Session Patio 15-26    
14h30 Mini-Symposia    
Stochastic Computation and Complexity 2
Amphi 25
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)
MCM for reactor physics 1
24-25 S. 101
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 particle-tracing Monte Carlo methods
Benjamin Dechenaux Percolation properties of the neutron population in nuclear reactors
PDMPs for high dimensional sampling: theory and application 1
15-25 S. 102
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 Zig-Zag Sampler
Ritabrata Dutta Exact sampling of scoring rule posterior using Gibbs Boomerang
Monte Carlo Methods for Bayesian inference and optimization
15-25 S.104
Savvas Melidonis Efficient Bayesian computation for low-photon 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
Wednesday 28    
10h30 Mini-Symposia    
Stochastic Computation and Complexity 3
Amphi 25
Daniel Rudolf Convergence and well-definedness of ellitpical slice sampling
Tomasz Bochacik On error bounds, optimality and exceptional sets for selected randomized schemes for ODEs
Sonja Cox Infinite-dimensional Wishart processes
Pierre Bras  Convergence of Langevin-Simulated Annealing Algorithms with Multiplicative Noise
High dimensional integration and approximation 1
24-25 S. 101
James Nichols Community detection with entropic regularization
Alexander Gilbert Density estimation in uncertainty quantification using quasi-Monte Carlo methods with preintegration
Michael Feischl A quasi-Monte Carlo data compression algorithm for machine learning
Vesa Kaarnioja On the Periodic Model of Uncertainty Quantification With Application to Bayesian Inverse Problems
Variance reduction techniques for rare events 2
15-25 S. 102
Eya Ben Amar State-dependent 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
Recent Progress in Langevin MC
15-25 S.104
Alain Durmus On the convergence of the Unadjusted and Metropolis Adjusted Langevin Algorithms
Tyler Farghly Adaptive Langevin Monte Carlo methods for heavy-tailed sampling via weighted functional inequalities
Sifan Liu Langevin Quasi-Monte Carlo
Konstantinos Zygalakis Accelerating MCMC for imaging science by using an implicit Langevin algorithm
14h Mini-Symposia & Contributed Talks    
Numerical methods in statistical physics 3
Amphi 25
Juliane U. Klamser Can Monte Carlo methods be used to simulate active-matter 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
MLMC techniques for discontinuous functionals 1
24-25 S. 101
Chiheb Ben Hammouda MLMC Combined with Numerical Smoothing for Efficient Probabilities Computation, Density Estimation, and Option Pricing
Abdul-Lateef Haji-Ali 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
On the power of iid information for (non-linear) approximation 2
15-25 S. 102
Art Owen Mean Dimension of Radial Basis Functions
Robert J. Kunsch Uniform Approximation of Finite Sequences with Randomized Algorithms
Fabian Taubert Dimension-Incremental Function Approximation Using Monte-Carlo Methods
Contributed talks 3
15-25 S.104
Matti Vihola Conditional particle filters with bridge backward sampling
Nabil Kahalé Unbiased time-average estimators for Markov chains
Randolf Altmeyer Polynomial time guarantees for sampling based posterior inference
Elena Sofia D'ambrosio  A Deep Learning Method for computing summary statistics of the filtering equation in the Stochastic Reaction Networks Setting
Thursday 29    
10h30 Mini-Symposia & Contributed Talks    
MCM for reactor physics 2
Amphi 25
Emma Horton A binary branching model with Moran-type interactions
Elod Pazman Comparison of Dynamic and Static Flux Estimators and Their Impact on Group Constant Production in the Time-Dependent Monte Carlo Reactor Code GUARDYAN
Alex Cox Twisted particle filters for neutron transport
Andrea Zoia Analysis of heterogeneous Markov media for particle transport problems
Nonreversible processes: theory and applications
24-25 S. 101
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
15-25 S. 102
Konstantinos Zygalakis Bayesian Inference with Data-Driven Image Priors Encoded by Neural Networks
Luke Shaw Rotation-based Integrators for HMC
Nicola Branchini Generalized Self-Normalized Importance Sampling
 L. Nagar & M. Parga Pazos Adaptive Integration Approach for Sampling with Hamiltonian Monte Carlo Based Methods
Contributed talks 4
15-25 S.104
Paul Dobson Accelerating MCMC using interacting Langevin models
Andreas Eberle Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension
Irene Tubikanec Network inference in a stochastic multi-population neural mass model via SMC-ABC
Sara Pérez-Vieites Adaptive Gaussian nested filter for joint parameter and state estimation in state-space models
12h30 Poster Session Patio 15-26    
14h30 Mini-Symposia    
Stochastic Computation and Complexity 4
Amphi 25
Michaela Szölgyenyi A higher order approximation method for jump-diffusion 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
Convergence results for kinetic samplers
24-25 S. 101
Lionel Riou-Durand 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 Space-time Poincaré-type Inequality
Sampling Schemes: Quality Measures, Point Generation, and Applications
15-25 S. 102
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 Super-polynomial Accuracy of Median-of-means
(Quasi-)MC Software
15-25 S.104
Aleksei Sorokin Collaborative Integrations with the QMCPy Framework
Anne Reinarz UM-Bridge
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
Friday 30th    
10h30 Mini-Symposia & Contributed Talks    
Stochastic Computation and Complexity 5
Amphi 25
Lukasz Stepien Adaptive step-size control for global approximation of SDEs driven by countably dimensional Wiener process 
Monika Eisenmann Domain decomposition methods for SPDEs
Sotirios Sabanis Adaptive stochastic optimizers, Euler-Krylov’s polygonal approximations and the training of neural nets
Stefan Heinrich Randomized Complexity of Vector-Valued Approximation
PDMPs for high dimensional sampling: theory and application 2
24-25 S. 101
Alexandre Bouchard-Cote PDMPs as Monte Carlo algorithms models
Nawaf Bou-Rabee Randomized Time Integrator for Unadjusted Hamiltonian MCMC
Peter A. Whalley Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics  
Torben Sell Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-Differentiable Priors
Exploring the intersections of importance sampling, MCMC, and optimization
15-25 S. 102
Juan Kuntz Particle-Based Algorithms for Maximum Likelihood Estimation of Latent Variable Models
Jimmy Olsson PaRISian particle Gibbs samplers for state and parameter learning in nonlinear state-space models
Víctor Elvira MCMC-driven adaptive importance samplers
Dootika Vats Comparing apples to oranges: a universal effective sample size
Contributed talk 5
15-25 S.104
Emil Loevbak  Adjoint Monte Carlo particle methods with reversible random number generators
Giorgos Vasdekis Pseudo-marginal Piecewise Deterministic Monte Carlo
Yu Guang Wang Applied Harmonic Analysis and Particle Dynamics for Designing Neural Message Passing on Graphs
Josef Leydold A Transformed Density Rejection Based Algorithm for Densities with Poles and Inflection Points
13h30 Mini-Symposia & Contributed Talks    
Numerical methods in statistical physics 4
Amphi 25
Michela Ottobre Uniform in time approximations of stochastic dynamics
Matthew Dobson Steady-State Solutions for Nonequilibrium Langevin Dynamics
Renato Spacek Extending the regime of linear response with synthetic forcings
Grigorios Pavliotis  On the Diffusive-Mean Field Limit for Weakly Interacting Diffusions Exhibiting Phase Transitions
High dimensional integration and approximation 2
24-25 S. 101
Abirami Srikumar Multi-level quasi-Monte 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 kernel-based high-dimensional approximation
MLMC techniques for discontinuous functionals 2
15-25 S. 102
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 PDE-constrained risk-averse optimization
Cedric Beschle CLMC techniques for elliptic PDEs with random discontinuities
Daniel Roth  Multilevel Monte Carlo Learning
Contributed Talks 6
15-25 S.104
Nicolas Chopin Higher-order stochastic integration through cubic stratification
Pierre L'Ecuyer Improved Versions of the Lattice Tester and LatMRG Software Tools
David Métivier The Robust Quasi Monte Carlo Method
Sergei Kucherenko Active Subspaces for Problems with Dependent Variables using QMC Sampling
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