A library for differentiable nonlinear optimization
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Updated
Aug 21, 2024 - Python
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 code repository for ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization (SIGGRAPH TOG 2023)
Safe robot learning
Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automotaic Control Laboratory, ETH Zurich.
Collection of differentiable methods for robotics applications implemented with Pytorch.
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