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A diverse suite of scalable reinforcement learning environments written in JAX for hardware-accelerated research.
A curated collection of Monte Carlo tree search research papers with implementations from top AI conferences.
A JAX + Flax implementation of physics-inspired graph neural networks for solving combinatorial optimization problems like Max-Cut and Maximum Independent Set.
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