Bayesian Learning via Neural Schrödinger-Föllmer Flows

20 November 2021

Papers citing "Bayesian Learning via Neural Schrödinger-Föllmer Flows"

10 / 10 papers shown

Title
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 51 0 0 03 Jan 2025
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 29 2 0 25 Oct 2024
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series Byoungwoo Park Hyungi Lee Juho Lee AI4TS 41 0 0 08 Oct 2024
Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park Jungwon Choi Sungbin Lim Juho Lee 45 3 0 31 May 2024
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design Kieran Didi Francisco Vargas Simon V. Mathis Vincent Dutordoir Emile Mathieu U. J. Komorowska Pietro Lió DiffM 25 13 0 14 Dec 2023
Improved sampling via learned diffusions Lorenz Richter Julius Berner DiffM 24 52 0 03 Jul 2023
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 172 160 0 21 Oct 2021
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 127 48 0 20 Oct 2020
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 191 498 0 11 Jun 2018
MCMC using Hamiltonian dynamics Radford M. Neal 132 3,263 0 09 Jun 2012