Stars
A Modular Toolkit for Robot Kinematic Optimization
An implementation of Proximal Policy Optimization to train a MuJoCo model of a rat body to imitate the movements of a real rat, using the same biomechanical model and data as in Aldarondo et al. (2…
Imitation learning benchmark focusing on complex locomotion tasks using MuJoCo.
A Python framework for accelerated simulation, data generation and spatial computing.
GPU-optimized version of the MuJoCo physics simulator, designed for NVIDIA hardware.
Implementation of STAC using MJX for GPU acceleration. Part of VNL project.
Brax + Pufferlib + CARBS for gpu-accelerated robotics RL
An open-source library for GPU-accelerated robot learning and sim-to-real transfer.
Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/
Goal-Conditioned Reinforcement Learning with JAX
world modeling challenge for humanoid robots
Optax is a gradient processing and optimization library for JAX.
K-Scale's library for programmatically interacting with OnShape
Fast and simple implementation of RL algorithms, designed to run fully on GPU.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
Hardware-Accelerated Reinforcement Learning Algorithms in pure Jax!
A playbook for systematically maximizing the performance of deep learning models.
SBX: Stable Baselines Jax (SB3 + Jax) RL algorithms
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
🏛️A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX • End-to-End JAX RL
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Export iMessage data + run iMessage Diagnostics
Massively parallel rigidbody physics simulation on accelerator hardware.
Multi-Joint dynamics with Contact. A general purpose physics simulator.
Real-time behaviour synthesis with MuJoCo, using Predictive Control