This is your work, valued
PhD student. Interested in Game AI, JAX-based RL, offline RL and exploration.
JAX-CORL. Clean single-file implementation of offline RL algorithms in JAX
182mahjax. A GPU-Accelerated Mahjong Simulator for RL in JAX
52remax-rl. [ICML2026] Official JAX code for Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying
13SymPO. [TMLR2026] Official code for "On Symmetric Losses for Policy Optimization with Noisy Preferences"
8PUORL. [RLC2025] Official code for "Offline Reinforcement Learning with Domain-Unlabeled Data"
5nissymori.github.io. HTML
3ReMAC. The Official JAX Code for "Retry Policy Gradients for Continuous Action Spaces"
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