A library for differentiable nonlinear optimization
-
Updated
Jan 15, 2024 - Python
A library for differentiable nonlinear optimization
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.
Official implementation of Auxiliary Learning by Implicit Differentiation [ICLR 2021]
Macros and functions to work with DSGE models.
Differentiable matrix factorizations using ImplicitDifferentiation.jl.
Implicit Differentiable Optimal Control (IDOC) with JAX
Code for our paper Demand Response Model Identification and Behavior Forecast with OptNet: a Gradient-based Approach.
Bilevel Hyperparameter Optimization with Implicit Differentiation
An end-to-end multimodal framework incorporating explicit knowledge graphs and OOD-detection. (NeurIPS23)
Add a description, image, and links to the implicit-differentiation topic page so that developers can more easily learn about it.
To associate your repository with the implicit-differentiation topic, visit your repo's landing page and select "manage topics."