A Python framework for accelerated simulation, data generation and spatial computing.
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Updated
Aug 3, 2025 - Python
A Python framework for accelerated simulation, data generation and spatial computing.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Hardware accelerated, batchable and differentiable optimizers in JAX.
torchbearer: A model fitting library for PyTorch
Robot kinematics implemented in pytorch
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Differentiable Finite Element Method with JAX
Comprehensive optical design, optimization, and analysis in Python, including GPU-accelerated and differentiable ray tracing via PyTorch.
Code for our NeurIPS 2022 paper
[ICLR 2021 top 3%] Is Attention Better Than Matrix Decomposition?
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
S2FFT: Differentiable and accelerated spherical transforms
Differentiable Computational Lithogrpahy Framework
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
A domain-specific probabilistic programming language for reasoning about reasoning
A differentiable bridge between phase space and Fock space
Safe Pontryagin Differentiable Programming (Safe PDP) is a new theoretical and algorithmic safe differentiable framework to solve a broad class of safety-critical learning and control tasks.
Universal, autodiff-native software components for Simulation Intelligence. 📦
dSGP4: differentiable SGP4. Supports differentiability, ML integration & embarassingly parallel computations
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