A library for differentiable nonlinear optimization
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Official repo for the paper "SAGE: SLAM with Appearance and Geometry Prior for Endoscopy" (ICRA 2022)
Mathematical Programming in JAX
Safe robot learning
Official code repository for ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization (SIGGRAPH TOG 2023)
Implementation and examples from Trajectory Optimization with Optimization-Based Dynamics https://arxiv.org/abs/2109.04928
[L4DC 2025] Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automatic Control Laboratory, ETH Zurich.
Differentiable curve and surface similarity measures.
Preliminary code for the paper "Learning Deterministic Surrogates for Robust Convex QCQPs".
Tutorial on Deep Declarative Networks
A fully vectorized PyTorch implementation of BLEU scores optimized for training neural networks.
Collection of differentiable methods for robotics applications implemented with Pytorch.
A fully vectorized PyTorch implementation of ROUGE scores optimized for training neural networks.
Add a description, image, and links to the differentiable-optimization topic page so that developers can more easily learn about it.
To associate your repository with the differentiable-optimization topic, visit your repo's landing page and select "manage topics."