2 citations · 2 across the 2 of their papers we have counts for
2 papers
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.LG2023★ 2 cited
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman +3
Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinfor…