| Monday 26 |
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| 10h45 |
Mini-symposia |
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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 |
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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 |
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| Tuesday 27 |
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| 10h30 |
Mini-symposia & Contributed talks |
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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 |
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| 14h30 |
Mini-Symposia |
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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 |
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| Wednesday 28 |
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| 10h30 |
Mini-Symposia |
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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 |
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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 |
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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 |
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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 |
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| Thursday 29 |
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| 10h30 |
Mini-Symposia & Contributed Talks |
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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 |
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| 14h30 |
Mini-Symposia |
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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 |
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| Friday 30th |
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| 10h30 |
Mini-Symposia & Contributed Talks |
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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 |
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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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