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cs.LG2025
gfnx: Fast and Scalable Library for Generative Flow Networks in JAX
Daniil Tiapkin, Artem Agarkov, Nikita Morozov +4
In this paper, we present gfnx, a fast and scalable package for training and evaluating Generative Flow Networks (GFlowNets) written in JAX. gfnx provides an extensive set of envir…
cs.LG2025
Adaptive Destruction Processes for Diffusion Samplers
Timofei Gritsaev, Nikita Morozov, Kirill Tamogashev +5
This paper explores the challenges and benefits of a trainable destruction process in diffusion samplers -- diffusion-based generative models trained to sample an unnormalised dens…
cs.LG2025
Revisiting Non-Acyclic GFlowNets in Discrete Environments
Nikita Morozov, Ian Maksimov, Daniil Tiapkin +1
Generative Flow Networks (GFlowNets) are a family of generative models that learn to sample objects from a given probability distribution, potentially known up to a normalizing con…