Showing 6 of 6 projects
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.
A metaheuristic optimization framework for solving complex combinatorial problems like N-queens and protein folding.
An algorithm that recommends pizza ordering options based on group size, slice size, and pizza shop menu.
An OR-Tools worker that enables solving optimization problems using distributed computing on the Golem network.
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