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Joint Bayesian Inference of Graphical Structure and Parameters with a
  Single Generative Flow Network

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

30 May 2023
T. Deleu
Mizu Nishikawa-Toomey
Jithendaraa Subramanian
Nikolay Malkin
Laurent Charlin
Yoshua Bengio
    BDL
ArXivPDFHTML

Papers citing "Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network"

43 / 43 papers shown
Title
Learning Decision Trees as Amortized Structure Inference
Mohammed Mahfoud
Ghait Boukachab
Michał Koziarski
A. Garcia
Stefan Bauer
Yoshua Bengio
Nikolay Malkin
BDL
38
0
0
10 Mar 2025
ACTIVA: Amortized Causal Effect Estimation without Graphs via Transformer-based Variational Autoencoder
Andreas Sauter
Saber Salehkaleybar
Aske Plaat
Erman Acar
CML
31
0
0
03 Mar 2025
Causal Discovery via Bayesian Optimization
Bao Duong
Sunil Gupta
Thin Nguyen
31
0
0
28 Jan 2025
Streaming Bayes GFlowNets
Streaming Bayes GFlowNets
Tiago da Silva
Daniel Augusto R. M. A. de Souza
Diego Mesquita
BDL
26
0
0
08 Nov 2024
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly
  Sampled Time Series
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
Giangiacomo Mercatali
André Freitas
Jie Chen
BDL
CML
AI4TS
18
1
0
17 Oct 2024
On Divergence Measures for Training GFlowNets
On Divergence Measures for Training GFlowNets
Tiago da Silva
Eliezer de Souza da Silva
Diego Mesquita
BDL
11
1
0
12 Oct 2024
Beyond Squared Error: Exploring Loss Design for Enhanced Training of
  Generative Flow Networks
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
Rui Hu
Yifan Zhang
Zhuoran Li
Longbo Huang
23
0
0
03 Oct 2024
Adaptive teachers for amortized samplers
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
39
2
0
02 Oct 2024
Enhancing Solution Efficiency in Reinforcement Learning: Leveraging
  Sub-GFlowNet and Entropy Integration
Enhancing Solution Efficiency in Reinforcement Learning: Leveraging Sub-GFlowNet and Entropy Integration
Siyi He
18
0
0
01 Oct 2024
Possible principles for aligned structure learning agents
Possible principles for aligned structure learning agents
Lancelot Da Costa
Tomáš Gavenčiak
David Hyland
Mandana Samiei
Cristian Dragos-Manta
Candice Pattisapu
Adeel Razi
Karl J. Friston
16
0
0
30 Sep 2024
Can a Bayesian Oracle Prevent Harm from an Agent?
Can a Bayesian Oracle Prevent Harm from an Agent?
Yoshua Bengio
Michael K. Cohen
Nikolay Malkin
Matt MacDermott
Damiano Fornasiere
Pietro Greiner
Younesse Kaddar
27
4
0
09 Aug 2024
Learning Dynamic Bayesian Networks from Data: Foundations, First
  Principles and Numerical Comparisons
Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons
Vyacheslav Kungurtsev
Fadwa Idlahcen
Petr Rysavý
Pavel Rytír
Ales Wodecki
30
1
0
25 Jun 2024
Flow of Reasoning:Training LLMs for Divergent Problem Solving with Minimal Examples
Flow of Reasoning:Training LLMs for Divergent Problem Solving with Minimal Examples
Fangxu Yu
Lai Jiang
Haoqiang Kang
Shibo Hao
Lianhui Qin
LRM
AI4CE
78
4
0
09 Jun 2024
Baking Symmetry into GFlowNets
Baking Symmetry into GFlowNets
George Ma
Emmanuel Bengio
Yoshua Bengio
Dinghuai Zhang
24
8
0
08 Jun 2024
Embarrassingly Parallel GFlowNets
Embarrassingly Parallel GFlowNets
Tiago da Silva
Luiz Max Carvalho
Amauri Souza
Samuel Kaski
Diego Mesquita
26
1
0
05 Jun 2024
Challenges and Considerations in the Evaluation of Bayesian Causal
  Discovery
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
Amir Mohammad Karimi Mamaghan
P. Tigas
Karl Henrik Johansson
Yarin Gal
Yashas Annadani
Stefan Bauer
CML
29
3
0
05 Jun 2024
Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
Haoran He
C. Chang
Huazhe Xu
Ling Pan
69
6
0
03 Jun 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani
P. Tigas
Stefan Bauer
Adam Foster
16
0
0
26 May 2024
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs
Ryan Thompson
Edwin V. Bonilla
Robert Kohn
24
0
0
24 May 2024
CausalPlayground: Addressing Data-Generation Requirements in
  Cutting-Edge Causality Research
CausalPlayground: Addressing Data-Generation Requirements in Cutting-Edge Causality Research
Andreas Sauter
Erman Acar
Aske Plaat
SyDa
CML
11
1
0
21 May 2024
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable
  AI Systems
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems
David Dalrymple
Joar Skalse
Yoshua Bengio
Stuart J. Russell
Max Tegmark
...
Clark Barrett
Ding Zhao
Zhi-Xuan Tan
Jeannette Wing
Joshua Tenenbaum
41
51
0
10 May 2024
Discrete Probabilistic Inference as Control in Multi-path Environments
Discrete Probabilistic Inference as Control in Multi-path Environments
T. Deleu
Padideh Nouri
Nikolay Malkin
Doina Precup
Yoshua Bengio
103
28
0
15 Feb 2024
Investigating Generalization Behaviours of Generative Flow Networks
Investigating Generalization Behaviours of Generative Flow Networks
Lazar Atanackovic
Emmanuel Bengio
AI4CE
12
2
0
07 Feb 2024
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
He Zhao
V. Kitsios
Terry O'Kane
Edwin V. Bonilla
CML
22
1
0
06 Feb 2024
Variational DAG Estimation via State Augmentation With Stochastic
  Permutations
Variational DAG Estimation via State Augmentation With Stochastic Permutations
Edwin V. Bonilla
P. Elinas
He Zhao
Maurizio Filippone
V. Kitsios
Terry O'Kane
CML
25
3
0
04 Feb 2024
PhyloGFN: Phylogenetic inference with generative flow networks
PhyloGFN: Phylogenetic inference with generative flow networks
Mingyang Zhou
Zichao Yan
Elliot Layne
Nikolay Malkin
Dinghuai Zhang
Moksh Jain
Mathieu Blanchette
Yoshua Bengio
11
6
0
12 Oct 2023
Amortizing intractable inference in large language models
Amortizing intractable inference in large language models
Marvin Schmitt
Moksh Jain
Daniel Habermann
Younesse Kaddar
Ullrich Kothe
Stefan T. Radev
Nikolay Malkin
AIFin
BDL
19
45
0
06 Oct 2023
Learning to Scale Logits for Temperature-Conditional GFlowNets
Learning to Scale Logits for Temperature-Conditional GFlowNets
Minsu Kim
Joohwan Ko
Taeyoung Yun
Dinghuai Zhang
Ling Pan
W. Kim
Jinkyoo Park
Emmanuel Bengio
Yoshua Bengio
AI4CE
10
21
0
04 Oct 2023
Expected flow networks in stochastic environments and two-player
  zero-sum games
Expected flow networks in stochastic environments and two-player zero-sum games
Marco Jiralerspong
Bilun Sun
Danilo Vucetic
Tianyu Zhang
Yoshua Bengio
Gauthier Gidel
Nikolay Malkin
15
5
0
04 Oct 2023
Local Search GFlowNets
Local Search GFlowNets
Minsu Kim
Taeyoung Yun
Emmanuel Bengio
Dinghuai Zhang
Yoshua Bengio
Sungsoo Ahn
Jinkyoo Park
11
32
0
04 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through
  partial trajectory optimization
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
Dinghuai Zhang
Ricky Tian Qi Chen
Cheng-Hao Liu
Aaron C. Courville
Yoshua Bengio
19
40
0
04 Oct 2023
Delta-AI: Local objectives for amortized inference in sparse graphical
  models
Delta-AI: Local objectives for amortized inference in sparse graphical models
J. Falet
Hae Beom Lee
Nikolay Malkin
Chen Sun
Dragos Secrieru
Thomas Jiralerspong
Dinghuai Zhang
Guillaume Lajoie
Yoshua Bengio
29
6
0
03 Oct 2023
Human-in-the-Loop Causal Discovery under Latent Confounding using
  Ancestral GFlowNets
Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets
Tiago da Silva
Eliezer de Souza da Silva
Adèle Ribeiro
António Góis
Dominik Heider
Samuel Kaski
Diego Mesquita
CML
28
6
0
21 Sep 2023
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Quang-Duy Tran
Phuoc Nguyen
Bao Duong
Thin Nguyen
11
2
0
04 Sep 2023
Generative Flow Networks: a Markov Chain Perspective
Generative Flow Networks: a Markov Chain Perspective
T. Deleu
Yoshua Bengio
BDL
8
8
0
04 Jul 2023
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems
  with GFlowNets
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets
Dinghuai Zhang
H. Dai
Nikolay Malkin
Aaron Courville
Yoshua Bengio
L. Pan
11
36
0
26 May 2023
CFlowNets: Continuous Control with Generative Flow Networks
CFlowNets: Continuous Control with Generative Flow Networks
Yinchuan Li
Shuang Luo
Haozhi Wang
Jianye Hao
79
20
0
04 Mar 2023
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
Muralikrishnna G. Sethuraman
Romain Lopez
Ramkumar Veppathur Mohan
Faramarz Fekri
Tommaso Biancalani
Jan-Christian Hütter
CML
21
11
0
04 Jan 2023
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and
  Variational Bayes
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes
Mizu Nishikawa-Toomey
T. Deleu
Jithendaraa Subramanian
Yoshua Bengio
Laurent Charlin
BDL
CML
11
29
0
04 Nov 2022
Learning Latent Structural Causal Models
Learning Latent Structural Causal Models
Jithendaraa Subramanian
Yashas Annadani
Ivaxi Sheth
Nan Rosemary Ke
T. Deleu
Stefan Bauer
Derek Nowrouzezahrai
Samira Ebrahimi Kahou
CML
17
7
0
24 Oct 2022
GFlowNets and variational inference
GFlowNets and variational inference
Nikolay Malkin
Salem Lahlou
T. Deleu
Xu Ji
J. E. Hu
Katie Everett
Dinghuai Zhang
Yoshua Bengio
BDL
127
77
0
02 Oct 2022
Trajectory balance: Improved credit assignment in GFlowNets
Trajectory balance: Improved credit assignment in GFlowNets
Nikolay Malkin
Moksh Jain
Emmanuel Bengio
Chen Sun
Yoshua Bengio
142
165
0
31 Jan 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
Chris Cundy
Aditya Grover
Stefano Ermon
CML
32
71
0
06 Dec 2021
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