Monte Carlo Seminar

Семинар по методу Монте-Карло | Рокко Каприо | Оптимизация и выборка, EM-метод и связанные с ним ...

Семинар по методу Монте-Карло | Рокко Каприо | Оптимизация и выборка, EM-метод и связанные с ним ...
Monte Carlo Seminar| Guan-Horng Liu|Sampling with Schrödinger Bridge—An Adjoint-Matching Perspective

Monte Carlo Seminar| Guan-Horng Liu|Sampling with Schrödinger Bridge—An Adjoint-Matching Perspective
Monte Carlo Seminar| Sam Livingstone| New preconditioning theory and methodology for MCMC sampling

Monte Carlo Seminar| Sam Livingstone| New preconditioning theory and methodology for MCMC sampling
Monte Carlo Seminar| Filippo Ascolani|Coordorinate-wise MCMC for structured high-dim Bayesian models

Monte Carlo Seminar| Filippo Ascolani|Coordorinate-wise MCMC for structured high-dim Bayesian models
Monte Carlo Seminar| Giorgos Vasdekis| Sampling with time-changed Markov processes

Monte Carlo Seminar| Giorgos Vasdekis| Sampling with time-changed Markov processes
Monte Carlo Seminar| Alex Shestopaloff| Generalised Bayesian online learning in non-stationary envs.

Monte Carlo Seminar| Alex Shestopaloff| Generalised Bayesian online learning in non-stationary envs.
Monte Carlo Seminar| Ruqi Zhang| Gradient-based discrete sampling: algorithms and applications

Monte Carlo Seminar| Ruqi Zhang| Gradient-based discrete sampling: algorithms and applications
Monte Carlo Seminar| Michael Albergo| Non-equilibrium transport and tilt matching for sampling

Monte Carlo Seminar| Michael Albergo| Non-equilibrium transport and tilt matching for sampling
Monte Carlo Seminar| Yian Ma| MCMC, VI, and reverse diffusion Monte Carlo

Monte Carlo Seminar| Yian Ma| MCMC, VI, and reverse diffusion Monte Carlo
Monte Carlo Seminar| Alexandare Bouchard-Côté| Computational Lebesgue Integration

Monte Carlo Seminar| Alexandare Bouchard-Côté| Computational Lebesgue Integration
MC Seminar| Alain Durmus| Toward principled inference and convergence guarantees in diffusion models

MC Seminar| Alain Durmus| Toward principled inference and convergence guarantees in diffusion models
Monte Carlo Seminar| Vivek Roy|A Riemannian manifold approach to informed MCMC sampling|May 20, 2025

Monte Carlo Seminar| Vivek Roy|A Riemannian manifold approach to informed MCMC sampling|May 20, 2025
Monte Carlo Seminar|Ning Ning| Convergence of Dirichlet forms for MCMC optimal scaling

Monte Carlo Seminar|Ning Ning| Convergence of Dirichlet forms for MCMC optimal scaling
Monte Carlo Seminar|Quan Zhou| Sampling complexity of high-dim structure learning and other problems

Monte Carlo Seminar|Quan Zhou| Sampling complexity of high-dim structure learning and other problems
MC Seminar| Yuexi Wang| Optimal Transport-Based Generative Models for Bayesian Posterior Sampling

MC Seminar| Yuexi Wang| Optimal Transport-Based Generative Models for Bayesian Posterior Sampling
Monte Carlo Seminar| Qiang Liu| Rectified Flow

Monte Carlo Seminar| Qiang Liu| Rectified Flow
Monte Carlo Seminar| Dootika Vats| MCMC Importance Sampling via Moreau-Yosida Envelopes

Monte Carlo Seminar| Dootika Vats| MCMC Importance Sampling via Moreau-Yosida Envelopes
Monte Carlo Seminar|Chenyang Zhong|A hit and run approach for sampling and analyzing ranking models

Monte Carlo Seminar|Chenyang Zhong|A hit and run approach for sampling and analyzing ranking models
Monte Carlo Seminar| Yuchen Wu| Theoretical advances in diffusion models

Monte Carlo Seminar| Yuchen Wu| Theoretical advances in diffusion models
Monte Carlo Seminar| Saifuddin Syed| Scalable sampling of multi-model distributions using SMC

Monte Carlo Seminar| Saifuddin Syed| Scalable sampling of multi-model distributions using SMC
Monte Carlo Seminar| Sinho Chewi| A local error framework in KL divergence via shifted composition

Monte Carlo Seminar| Sinho Chewi| A local error framework in KL divergence via shifted composition
Monte Carlo Seminar| Bob Carpenter| How does Stan work?

Monte Carlo Seminar| Bob Carpenter| How does Stan work?
Monte Carlo Seminar|Max Welling| A Variational Bayesian Method for AR and Recurrent Models

Monte Carlo Seminar|Max Welling| A Variational Bayesian Method for AR and Recurrent Models
Monte Carlo Seminar| Galin Jones| Reliable Metropolis-Hastings in the High-Dim, Large-Sample Regime

Monte Carlo Seminar| Galin Jones| Reliable Metropolis-Hastings in the High-Dim, Large-Sample Regime
Monte Carlo Seminar| Sam Power| Convergence of Random Walk Metropolis: Perspectives fr Isoperimetry

Monte Carlo Seminar| Sam Power| Convergence of Random Walk Metropolis: Perspectives fr Isoperimetry
Monte Carlo Seminar| Nicolas Chopin| A connection between Tempering SMC and Entropic Mirror Descent

Monte Carlo Seminar| Nicolas Chopin| A connection between Tempering SMC and Entropic Mirror Descent
Monte Carlo Seminar| Haotian Jiang| Quasi Monte Carlo via Algorithmic Discrepancy Theory|Feb 4, 2025

Monte Carlo Seminar| Haotian Jiang| Quasi Monte Carlo via Algorithmic Discrepancy Theory|Feb 4, 2025
Monte Carlo Seminar| Matti Vihola| An invitation to adaptive MCMC convergence theory| Jan. 28, 25

Monte Carlo Seminar| Matti Vihola| An invitation to adaptive MCMC convergence theory| Jan. 28, 25
Monte Carlo Seminar| Kuikui Liu| On Spectral Independence and Applications| Jan 21, 2025

Monte Carlo Seminar| Kuikui Liu| On Spectral Independence and Applications| Jan 21, 2025
Monte Carlo Seminar| Yuansi Chen| Regularized Dikin Walks for Sampling Truncated Logconcave Measures

Monte Carlo Seminar| Yuansi Chen| Regularized Dikin Walks for Sampling Truncated Logconcave Measures