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Bayesian Structure Learning with Generative Flow Networks

28 February 2022

Stefan Bauer

Papers citing "Bayesian Structure Learning with Generative Flow Networks"

37 / 37 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 195 1 0 28 Apr 2025
Process-Supervised LLM Recommenders via Flow-guided Tuning Chongming Gao Mengyao Gao Chenxiao Fan Shuai Yuan Wentao Shi Xiangnan He 108 5 0 10 Mar 2025
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation Mohit Pandey G. Subbaraj Artem Cherkasov Martin Ester Emmanuel Bengio AI4CE 117 1 0 08 Mar 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 143 0 0 28 Jan 2025
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Zhen Liu Tim Z. Xiao Weiyang Liu Yoshua Bengio Dinghuai Zhang 176 5 0 10 Dec 2024
Amortized Inference of Causal Models via Conditional Fixed-Point Iterations Divyat Mahajan Jannes Gladrow Agrin Hilmkil Cheng Zhang M. Scetbon 102 2 0 08 Oct 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 450 7 0 02 Oct 2024
Neural Spacetimes for DAG Representation Learning Haitz Sáez de Ocáriz Borde Anastasis Kratsios Marc T. Law Xiaowen Dong Michael Bronstein CML 89 2 0 25 Aug 2024
Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets Haoran He C. Chang Huazhe Xu Ling Pan 145 7 0 03 Jun 2024
Learning Latent Graph Structures and their Uncertainty A. Manenti Daniele Zambon Cesare Alippi BDL 149 1 0 30 May 2024
Learning diverse attacks on large language models for robust red-teaming and safety tuning Seanie Lee Minsu Kim Lynn Cherif David Dobre Juho Lee ... Kenji Kawaguchi Gauthier Gidel Yoshua Bengio Nikolay Malkin Moksh Jain AAML 116 19 0 28 May 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 106 1 0 22 Feb 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 169 26 0 07 Feb 2024
Investigating Generalization Behaviours of Generative Flow Networks Lazar Atanackovic Emmanuel Bengio AI4CE 65 4 0 07 Feb 2024
Differentiable Causal Discovery Under Latent Interventions Gonccalo R. A. Faria André F. T. Martins Mário A. T. Figueiredo BDL CML OOD 74 23 0 04 Mar 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 88 73 0 06 Dec 2021
GFlowNet Foundations Yoshua Bengio Salem Lahlou T. Deleu J. E. Hu Mo Tiwari Emmanuel Bengio 55 236 0 17 Nov 2021
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures Yashas Annadani Jonas Rothfuss Alexandre Lacoste Nino Scherrer Anirudh Goyal Yoshua Bengio Stefan Bauer BDL CML 77 48 0 14 Jun 2021
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio Moksh Jain Maksym Korablyov Doina Precup Yoshua Bengio 101 331 0 08 Jun 2021
DiBS: Differentiable Bayesian Structure Learning Lars Lorch Jonas Rothfuss Bernhard Schölkopf Andreas Krause 50 87 0 25 May 2021
Towards Scalable Bayesian Learning of Causal DAGs Jussi Viinikka Antti Hyttinen J. Pensar Mikko Koivisto CML 77 34 0 30 Sep 2020
Differentiable Causal Discovery from Interventional Data P. Brouillard Sébastien Lachapelle Alexandre Lacoste Simon Lacoste-Julien Alexandre Drouin CML 64 188 0 03 Jul 2020
Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention Angelos Katharopoulos Apoorv Vyas Nikolaos Pappas Franccois Fleuret 201 1,771 0 29 Jun 2020
Causal Discovery with Reinforcement Learning Shengyu Zhu Ignavier Ng Zhitang Chen CML 58 240 0 11 Jun 2019
Deep Reinforcement Learning and the Deadly Triad H. V. Hasselt Yotam Doron Florian Strub Matteo Hessel Nicolas Sonnerat Joseph Modayil OffRL 81 230 0 06 Dec 2018
Efficient Sampling and Structure Learning of Bayesian Networks Jack Kuipers Polina Suter G. Moffa TPM CML 47 69 0 21 Mar 2018
Learning Deep Generative Models of Graphs Yujia Li Oriol Vinyals Chris Dyer Razvan Pascanu Peter W. Battaglia GNN AI4CE 194 662 0 08 Mar 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning Xun Zheng Bryon Aragam Pradeep Ravikumar Eric Xing NoLa CML OffRL 99 942 0 04 Mar 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 701 131,652 0 12 Jun 2017
Partition MCMC for inference on acyclic digraphs Jack Kuipers G. Moffa 116 91 0 20 Apr 2015
Addendum on the scoring of Gaussian directed acyclic graphical models Jack Kuipers G. Moffa David Heckerman 135 71 0 27 Feb 2014
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 117 3,982 0 27 Feb 2013
Learning Gaussian Networks D. Geiger David Heckerman TPM 73 500 0 27 Feb 2013
Data Analysis with Bayesian Networks: A Bootstrap Approach N. Friedman M. Goldszmidt A. Wyner TPM 89 377 0 23 Jan 2013
Structured Priors for Structure Learning Vikash K. Mansinghka Charles Kemp Thomas Griffiths J. Tenenbaum CML 125 81 0 27 Jun 2012
Advances in exact Bayesian structure discovery in Bayesian networks Mikko Koivisto TPM 60 90 0 27 Jun 2012
Bayesian structure learning using dynamic programming and MCMC Daniel Eaton Kevin P. Murphy 82 136 0 20 Jun 2012