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.
Mathematical Programming in JAX
Official repo for the paper "SAGE: SLAM with Appearance and Geometry Prior for Endoscopy" (ICRA 2022)
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.
A library for soft differentiable relaxations of common JAX functions.
Preliminary code for the paper "Learning Deterministic Surrogates for Robust Convex QCQPs".
A library for soft differentiable relaxations of common PyTorch functions.
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.
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