Gareth Roberts
University of Warwick
Diffusive Behaviour Of Non-reversible Mcmc With Application To Simulated Tempering.

Jonathan Weare
NYU
Convergence Of Unadjusted Langevin In High-Dimensions: Delocalization Of Bias

Andreas Eberle
Bonn
Non-reversible Lifts Of Reversible Diffusion Processes And Relaxation Times

Alain Durmus
Ecole Polytechnique

Valentin de Bortoli
Google DeepMind

Holden Lee
Johns Hopkins
Efficiently Learning And Sampling Multimodal Distributions With Data-based Initialization

Yuchen Wu
Wharton
Provably Efficient Posterior Sampling Via Measure Decomposition

Eric Vigoda
UC Santa Barbara
Optimal Mixing Via Spectral Independence: Sampling Independent Sets And Colorings

Daniel Lacker
Columbia University
Projected Langevin Dynamics And A Gradient Flow For Entropic Optimal Transport

Ashia Wilson
MIT
High-accuracy Sampling From Constrained Spaces: An Optimization Perspective

Jianfeng Lu
Duke
Twisted Path Particle Filter

Anna Korba
CREST/ENSAE
Implicit Diffusion: Efficient Optimization Through Stochastic Sampling

Smita Krishnaswamy
Yale
Geometry-aware Generative Autoencoders For Sample Generation On Manifolds

Matt Hoffman
Google DeepMind
Running Many-chain Mcmc On Cheap Gpus

Wesley Pegden
CMU
Probability Spaces Driven By Geometric Constraints

Bob Carpenter
Flatiron Institute
Gist: Gibbs Self Tuning For Locally Adaptive Hamiltonian Monte Carlo

Nawaf Bou-Rabee
Rutgers
Mixing Of The No-u-turn Sampler And The Geometry Of Gaussian Concentration

Kevin Tian
UT Austin
Algorithmic Aspects Of The Log-laplace Transform And A Non-euclidean Proximal Sampler

Nima Anari
Stanford University
Parallel Sampling Via Auto-speculation

Cheng Lu
OpenAI
Scalable Fast Sampling Methods For Diffusion Models