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
Macros and functions to work with DSGE models.
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]
Differentiable matrix factorizations using ImplicitDifferentiation.jl.
Implicit Differentiable Optimal Control (IDOC) with JAX
A differentiable Frank-Wolfe solver - minimal and in pure Julia.
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 vision-language framework incorporating explicit knowledge graphs and OOD-detection. (NeurIPS 23)
Implicit-differentiation experiments for parametrized Hamiltonians and bilevel Max-Cut optimization.
SILVA Networks is a Python package for extended deep equilibrium layers, fixed-point solvers, implicit differentiation, structured operators, diagnostics, and reproducible research notebooks.
To associate your repository with the implicit-differentiation topic, visit your repo's landing page and select "manage topics."