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cs.LG2025
A Theory of Multi-Agent Generative Flow Networks
Leo Maxime Brunswic, Haozhi Wang, Shuang Luo +3
Generative flow networks utilize a flow-matching loss to learn a stochastic policy for generating objects from a sequence of actions, such that the probability of generating a patt…
cs.LG2025
Ergodic Generative Flows
Leo Maxime Brunswic, Mateo Clemente, Rui Heng Yang +3
Generative Flow Networks (GFNs) were initially introduced on directed acyclic graphs to sample from an unnormalized distribution density. Recent works have extended the theoretical…
cs.LG2023
A Theory of Non-Acyclic Generative Flow Networks
Leo Maxime Brunswic, Yinchuan Li, Yushun Xu +2
GFlowNets is a novel flow-based method for learning a stochastic policy to generate objects via a sequence of actions and with probability proportional to a given positive reward.…