The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

Your favourite classical machine learning algos on the GPU/TPU

An Open-Ended Agentic Simulator

Awesome Open-ended AI

Research Papers and Code Repository on the Integration of Evolutionary Algorithms and Reinforcement Learning

Code for Discovering Preference Optimization Algorithms with and for Large Language Models

Code for Discovering Preference Optimization Algorithms with and for Large Language Models

Accelerated minigrid environments with JAX

POPGym Library in JAX

(Crafter + NetHack) in JAX. ICML 2024 Spotlight.

Efficient implementations of state-of-the-art linear attention models in Pytorch 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 🏎️

Scalable Opponent Shaping Experiments in JAX

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)]

Baselines for gymnax 🤖

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

Code for Discovered Policy Optimisation (NeurIPS 2022)

Code for Adversarial Cheap Talk (ICML 2023)

Mutation-guided mutation-based fuzz testing