Stars
Reinforcement learning on general 2D physics environments in JAX. ICLR 2025 Oral.
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Your favourite classical machine learning algos on the GPU/TPU
Drop-in environment replacements that make your RL algorithm train faster.
Research Papers and Code Repository on the Integration of Evolutionary Algorithms and Reinforcement Learning
SakanaAI / DiscoPOP
Forked from luchris429/DiscoPOPCode for Discovering Preference Optimization Algorithms with and for Large Language Models
Code for Discovering Preference Optimization Algorithms with and for Large Language Models
Hardware-Accelerated Reinforcement Learning Algorithms in pure Jax!
(Crafter + NetHack) in JAX. ICML 2024 Spotlight.
🚀 Efficient implementations of state-of-the-art linear attention models in Torch and Triton
jax-triton contains integrations between JAX and OpenAI Triton
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️
Contains JAX implementation of algorithms for inverse reinforcement learning
Efficient baselines for autocurricula in JAX.
Benchmarking RL for POMDPs in Pure JAX [Code for "Structured State Space Models for In-Context Reinforcement Learning" (NeurIPS 2023)]
Analysis & Experiment Configurations for NEB
🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
Sample Complexity of Model-Free Opponent Shaping
Implementation of ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages