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GPU-optimized version of the MuJoCo physics simulator, designed for NVIDIA hardware.
ICRA2025: OpenGS-SLAM: Open-Set Dense Semantic SLAM with 3D Gaussian Splatting for Object-Level Scene Understanding
The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.
[CoRL 2023] This repository contains data generation and training code for Scaling Up & Distilling Down
A scene exporter from Blender to the MuJoCo physics engine
PDDLStream: Integrating Symbolic Planners and Blackbox Samplers
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion Models
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Python scripts for the Segment Anythin 2 (SAM2) model in ONNX
Official implementation for the paper "Full-Order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing". DIAL-MPC is a novel sampling-based MPC framework for legged …
C++ cross-platform wrapper around dynamic loading of shared libraries (dll, so, dylib)
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained …
A next-gen Lagrange-Newton (SQP + barrier) solver for nonconvex constrained optimization
[SIGGRAPH2022] Approximate Convex Decomposition for 3D Meshes with Collision-Aware Concavity and Tree Search
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
[RSS 2024] AdaptiGraph: Material-Adaptive Graph-Based Neural Dynamics for Robotic Manipulation
Toolkit for generating code from symbolic math expressions.
Symbolic planners for problems and domains specified in PDDL.
[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation