implicit-differentiation

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.