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The Generative Flow Network is a probabilistic framework where an agent learns a stochastic policy for object generation, such that the probability of generating an object is proportional to a given reward function.
Planning by probabilistic inference
Hagai Attias · 2003
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Modeling purposeful adaptive behavior with the principle of maximum causal entropy
Brian D. Ziebart · 2010
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
Earlier work this paper cites.
Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
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Reinforcement learning with deep energy-based policies
Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, and Sergey Levine · 2017
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Diversity in recommender systems–a survey
Matevž Kunaver and Tomaž Požrl · 2017
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Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Exploration by random network distillation
Yuri Burda, Harrison Edwards, Amos Storkey, and Oleg Klimov · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Grandmaster level in starcraft ii using multi-agent reinforcement learning
Mars: Markov molecular sampling for multi-objective drug discovery
Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang, Yong Yu, and Lei Li · 2020
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Task-oriented dialog systems that consider multiple appropriate responses under the same context
Yichi Zhang, Zhijian Ou, and Zhou Yu · 2020
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Reward is enough
David Silver, Satinder Singh, Doina Precup, and Richard S Sutton · 2021
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Noveld: A simple yet effective exploration criterion
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E Gonzalez, and Yuandong Tian · 2021
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Bayesian structure learning with generative flow networks
Tristan Deleu, Ant’onio G’ois, Chris C. Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, and Yoshua Bengio · 2022
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Oriol Vinyals, Igor Babuschkin, Wojciech M Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H Choi, Richard Powell, Timo Ewalds, Petko Georgiev, et al · 2019
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Learning discrete energy-based models via auxiliary-variable local exploration
Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, and Dale Schuurmans · 2020
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Flow network based generative models for non-iterative diverse candidate generation
Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, and Yoshua Bengio
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Yoshua Bengio, Tristan Deleu, Edward J Hu, Salem Lahlou, Mo Tiwari, and Emmanuel Bengio
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Biological sequence design with gflownets
Moksh Jain, Emmanuel Bengio, Alex García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Micheal Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, and Yoshua Bengio
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Biological sequence design with gflownets
Moksh Jain, Emmanuel Bengio, Alex Hernandez-Garcia, Jarrid Rector-Brooks, Bonaventure FP Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, et al
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Unifying generative models with gflownets
Dinghuai Zhang, Ricky T. Q. Chen, Nikolay Malkin, and Yoshua Bengio
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Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, and Yoshua Bengio · 2022
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