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Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
Neural Information Processing Systems (NeurIPS), 2023
30 May 2023
T. Deleu
Mizu Nishikawa-Toomey
Jithendaraa Subramanian
Nikolay Malkin
Laurent Charlin
Yoshua Bengio
BDL
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Papers citing
"Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network"
39 / 39 papers shown
Can Knowledge-Graph-based Retrieval Augmented Generation Really Retrieve What You Need?
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535
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Adaptive Destruction Processes for Diffusion Samplers
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Nikita Morozov
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355
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0
02 Jun 2025
Learning Decision Trees as Amortized Structure Inference
Mohammed Mahfoud
Ghait Boukachab
Michał Koziarski
A. Garcia
Stefan Bauer
Yoshua Bengio
Nikolay Malkin
BDL
350
1
0
10 Mar 2025
Causal Discovery via Bayesian Optimization
International Conference on Learning Representations (ICLR), 2025
Bao Duong
Sunil Gupta
Thin Nguyen
388
1
0
28 Jan 2025
Streaming Bayes GFlowNets
Neural Information Processing Systems (NeurIPS), 2024
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Diego Mesquita
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431
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0
08 Nov 2024
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
Neural Information Processing Systems (NeurIPS), 2024
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André Freitas
Jie Chen
BDL
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AI4TS
531
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0
17 Oct 2024
On Divergence Measures for Training GFlowNets
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Tiago da Silva
Eliezer de Souza da Silva
Diego Mesquita
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507
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0
12 Oct 2024
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
International Conference on Learning Representations (ICLR), 2024
Rui Hu
Yifan Zhang
Zhuoran Li
Longbo Huang
328
6
0
03 Oct 2024
Adaptive teachers for amortized samplers
International Conference on Learning Representations (ICLR), 2024
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Sanghyeok Choi
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Jinkyoo Park
Nikolay Malkin
Yoshua Bengio
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0
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Enhancing Solution Efficiency in Reinforcement Learning: Leveraging Sub-GFlowNet and Entropy Integration
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237
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Possible Principles for Aligned Structure Learning Agents
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Tomáš Gavenčiak
David Hyland
Mandana Samiei
Cristian Dragos-Manta
Candice Pattisapu
Adeel Razi
Karl J. Friston
578
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0
30 Sep 2024
Can a Bayesian Oracle Prevent Harm from an Agent?
Conference on Uncertainty in Artificial Intelligence (UAI), 2024
Yoshua Bengio
Michael K. Cohen
Nikolay Malkin
Matt MacDermott
Damiano Fornasiere
Pietro Greiner
Younesse Kaddar
472
9
0
09 Aug 2024
Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons
Vyacheslav Kungurtsev
Fadwa Idlahcen
Petr Rysavý
Pavel Rytíř
Ales Wodecki
498
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0
25 Jun 2024
Flow of Reasoning:Training LLMs for Divergent Problem Solving with Minimal Examples
Fangxu Yu
Lai Jiang
Haoqiang Kang
Shibo Hao
Lianhui Qin
LRM
AI4CE
801
10
0
09 Jun 2024
Baking Symmetry into GFlowNets
George Ma
Emmanuel Bengio
Yoshua Bengio
Dinghuai Zhang
285
16
0
08 Jun 2024
Embarrassingly Parallel GFlowNets
Tiago da Silva
Luiz Max Carvalho
Amauri Souza
Samuel Kaski
Diego Mesquita
415
3
0
05 Jun 2024
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
321
6
0
05 Jun 2024
Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
Haoran He
C. Chang
Huazhe Xu
Ling Pan
631
9
0
03 Jun 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
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P. Tigas
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383
4
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26 May 2024
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SyDa
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316
3
0
21 May 2024
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
405
106
0
10 May 2024
Discrete Probabilistic Inference as Control in Multi-path Environments
T. Deleu
Padideh Nouri
Nikolay Malkin
Doina Precup
Yoshua Bengio
430
42
0
15 Feb 2024
Investigating Generalization Behaviours of Generative Flow Networks
Lazar Atanackovic
Emmanuel Bengio
AI4CE
374
8
0
07 Feb 2024
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
He Zhao
V. Kitsios
Terry O'Kane
Edwin V. Bonilla
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448
2
0
06 Feb 2024
Permutation-based Inference for Variational Learning of Directed Acyclic Graphs
Edwin V. Bonilla
P. Elinas
He Zhao
Maurizio Filippone
V. Kitsios
Terry O'Kane
CML
501
5
0
04 Feb 2024
PhyloGFN: Phylogenetic inference with generative flow networks
International Conference on Learning Representations (ICLR), 2023
Mingyang Zhou
Zichao Yan
Elliot Layne
Nikolay Malkin
Dinghuai Zhang
Moksh Jain
Mathieu Blanchette
Yoshua Bengio
296
31
0
12 Oct 2023
Amortizing intractable inference in large language models
International Conference on Learning Representations (ICLR), 2023
Marvin Schmitt
Moksh Jain
Daniel Habermann
Younesse Kaddar
Ullrich Kothe
Stefan T. Radev
Nikolay Malkin
AIFin
BDL
461
89
0
06 Oct 2023
Learning to Scale Logits for Temperature-Conditional GFlowNets
International Conference on Machine Learning (ICML), 2023
Minsu Kim
Joohwan Ko
Taeyoung Yun
Dinghuai Zhang
Ling Pan
W. Kim
Jinkyoo Park
Emmanuel Bengio
Yoshua Bengio
AI4CE
390
30
0
04 Oct 2023
Expected flow networks in stochastic environments and two-player zero-sum games
International Conference on Learning Representations (ICLR), 2023
Marco Jiralerspong
Bilun Sun
Danilo Vucetic
Tianyu Zhang
Yoshua Bengio
Gauthier Gidel
Nikolay Malkin
411
10
0
04 Oct 2023
Local Search GFlowNets
International Conference on Learning Representations (ICLR), 2023
Minsu Kim
Taeyoung Yun
Emmanuel Bengio
Dinghuai Zhang
Yoshua Bengio
SungSoo Ahn
Jinkyoo Park
403
58
0
04 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
International Conference on Learning Representations (ICLR), 2023
Dinghuai Zhang
Ricky Tian Qi Chen
Cheng-Hao Liu
Aaron C. Courville
Yoshua Bengio
473
64
0
04 Oct 2023
Delta-AI: Local objectives for amortized inference in sparse graphical models
International Conference on Learning Representations (ICLR), 2023
Jean-Pierre Falet
Hae Beom Lee
Nikolay Malkin
Chen Sun
Dragos Secrieru
Thomas Jiralerspong
Dinghuai Zhang
Guillaume Lajoie
Yoshua Bengio
389
8
0
03 Oct 2023
Expert-Aided Causal Discovery of Ancestral Graphs
Tiago da Silva
Bruna Bazaluk
Eliezer de Souza da Silva
António Góis
Dominik Heider
Samuel Kaski
Diego Mesquita
Adèle H. Ribeiro
Adèle Helena Ribeiro
CML
553
8
0
21 Sep 2023
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Industrial Conference on Data Mining (IDM), 2023
Quang-Duy Tran
Phuoc Nguyen
Bao Duong
Thin Nguyen
343
4
0
04 Sep 2023
Generative Flow Networks: a Markov Chain Perspective
T. Deleu
Yoshua Bengio
BDL
324
11
0
04 Jul 2023
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets
Dinghuai Zhang
H. Dai
Nikolay Malkin
Aaron Courville
Yoshua Bengio
L. Pan
359
51
0
26 May 2023
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
441
34
0
04 Nov 2022
Learning Latent Structural Causal Models
Jithendaraa Subramanian
Yashas Annadani
Ivaxi Sheth
Nan Rosemary Ke
T. Deleu
Stefan Bauer
Derek Nowrouzezahrai
Samira Ebrahimi Kahou
CML
270
7
0
24 Oct 2022
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