Productive, portable, and performant GPU programming in Python.
- Updated
Oct 6, 2025 - C++
Productive, portable, and performant GPU programming in Python.
Swift for TensorFlow
A Python framework for accelerated simulation, data generation and spatial computing.
10 differentiable physical simulators built with Taichi differentiable programming (DiffTaichi, ICLR 2020)
A general-purpose probabilistic programming system with programmable inference
High-performance automatic differentiation of LLVM and MLIR.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Fast and embedded solvers for nonlinear optimal control and nonlinear model predictive control
Hardware accelerated, batchable and differentiable optimizers in JAX.
A high-fidelity 3D face reconstruction library from monocular RGB image(s)
Swift for TensorFlow Deep Learning Library
Robot kinematics implemented in pytorch
torchbearer: A model fitting library for PyTorch
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types
Julia bindings for the Enzyme automatic differentiator
Differentiable Finite Element Method with JAX
Comprehensive optical design, optimization, and analysis in Python, including GPU-accelerated and differentiable ray tracing via PyTorch.
Code repository for our paper DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact
Code for our NeurIPS 2022 paper
Add a description, image, and links to the differentiable-programming topic page so that developers can more easily learn about it.
To associate your repository with the differentiable-programming topic, visit your repo's landing page and select "manage topics."