Preliminary code for the paper "Learning Deterministic Surrogates for Robust Convex QCQPs".
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Updated
May 20, 2024 - Jupyter Notebook
Preliminary code for the paper "Learning Deterministic Surrogates for Robust Convex QCQPs".
Collection of differentiable methods for robotics applications implemented with Pytorch.
Tutorial on Deep Declarative Networks
Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automotaic Control Laboratory, ETH Zurich.
Safe robot learning
Implementation and examples from Trajectory Optimization with Optimization-Based Dynamics https://arxiv.org/abs/2109.04928
Official code repository for ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization (SIGGRAPH TOG 2023)
Official repo for the paper "SAGE: SLAM with Appearance and Geometry Prior for Endoscopy" (ICRA 2022)
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
A library for differentiable nonlinear optimization
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