GFlowNets and variational inference

2 October 2022

Nikolay Malkin

Papers citing "GFlowNets and variational inference"

35 / 35 papers shown

Title
Accurate and Diverse LLM Mathematical Reasoning via Automated PRM-Guided GFlowNets Adam Younsi Abdalgader Abubaker M. Seddik Hakim Hacid Salem Lahlou LRM 152 1 0 28 Apr 2025
Less is More: Adaptive Program Repair with Bug Localization and Preference Learning Zhenlong Dai Bingrui Chen Zhuoluo Zhao Xiu Tang Sai Wu Chang Yao Zhipeng Gao Jingyuan Chen KELM 77 3 0 09 Mar 2025
FedGrAINS: Personalized SubGraph Federated Learning with Adaptive Neighbor Sampling Emir Ceyani Han Xie Baturalp Buyukates Carl Yang Salman Avestimehr FedML 223 0 0 22 Jan 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner Lorenz Richter Marcin Sendera Jarrid Rector-Brooks Nikolay Malkin OffRL 95 8 0 10 Jan 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 89 0 0 03 Jan 2025
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Zhen Liu Tim Z. Xiao Weiyang Liu Yoshua Bengio Dinghuai Zhang 153 5 0 10 Dec 2024
Adaptive teachers for amortized samplers Minsu Kim Sanghyeok Choi Taeyoung Yun Emmanuel Bengio Leo Feng Jarrid Rector-Brooks Sungsoo Ahn Jinkyoo Park Nikolay Malkin Yoshua Bengio 390 7 0 02 Oct 2024
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets Piotr Gaiñski Michał Koziarski Krzysztof Maziarz Marwin H. S. Segler Jacek Tabor Marek Śmieja 89 4 0 26 Jun 2024
Amortizing intractable inference in diffusion models for vision, language, and control S. Venkatraman Moksh Jain Luca Scimeca Minsu Kim Marcin Sendera ... Alexandre Adam Jarrid Rector-Brooks Yoshua Bengio Glen Berseth Nikolay Malkin 110 30 0 31 May 2024
Ant Colony Sampling with GFlowNets for Combinatorial Optimization Minsu Kim Sanghyeok Choi Hyeon-Seob Kim Jiwoo Son Jinkyoo Park Yoshua Bengio 79 30 0 11 Mar 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 100 24 0 07 Feb 2024
Unifying Generative Models with GFlowNets and Beyond Dinghuai Zhang Ricky T. Q. Chen Nikolay Malkin Yoshua Bengio BDL AI4CE 73 26 0 06 Sep 2022
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 55 21 0 21 Jun 2021
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio Moksh Jain Maksym Korablyov Doina Precup Yoshua Bengio 83 327 0 08 Jun 2021
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 177 350 0 20 Nov 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 168 50 0 20 Oct 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 67 908 0 08 Jul 2020
Variational f-divergence Minimization Mingtian Zhang Thomas Bird Raza Habib Tianlin Xu David Barber FedML 35 28 0 27 Jul 2019
The Thermodynamic Variational Objective Vaden Masrani T. Le Frank Wood 44 48 0 28 Jun 2019
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 570 3,112 0 04 Jun 2018
Semi-Implicit Variational Inference Mingzhang Yin Mingyuan Zhou BDL 69 128 0 28 May 2018
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines Cathy Wu Aravind Rajeswaran Yan Duan Vikash Kumar Alexandre M. Bayen Sham Kakade Igor Mordatch Pieter Abbeel OffRL 53 153 0 20 Mar 2018
Tighter Variational Bounds are Not Necessarily Better Tom Rainforth Adam R. Kosiorek T. Le Chris J. Maddison Maximilian Igl Frank Wood Yee Whye Teh DRL 138 198 0 13 Feb 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 317 1,367 0 12 Feb 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 151 690 0 15 Nov 2017
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation Will Grathwohl Dami Choi Yuhuai Wu Geoffrey Roeder David Duvenaud 89 300 0 31 Oct 2017
Operator Variational Inference Rajesh Ranganath Jaan Altosaar Dustin Tran David M. Blei 44 116 0 27 Oct 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 63 1,091 0 16 Aug 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 288 8,091 0 13 Aug 2016
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 244 1,245 0 01 Sep 2015
Stochastic Expectation Propagation Yingzhen Li Jose Miguel Hernandez-Lobato Richard Turner 122 115 0 12 Jun 2015
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 101 1,165 0 31 Dec 2013
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning Lex Weaver Nigel Tao 117 246 0 10 Jan 2013
Expectation Propagation for approximate Bayesian inference T. Minka 127 1,907 0 10 Jan 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 230 2,619 0 29 Jun 2012