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

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

Code base for SICNav T-RO paper and SICNav-Diffusion RA-L paper

MetaStyle: Three-Way Trade-Off Among Speed, Flexibility, and Quality in Neural Style Transfer

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)

Benchmark for bi-level optimization solvers

PyTorch implementation of "STNs" and "Delta-STNs".

Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"

Example Code for paper "Provably Faster Algorithms for Bilevel Optimization"

Formulations for the robust Resource-Constrained Project Scheduling Problem (RCPSP) using Pyomo modelling.

Deep Bilevel Learning. In ECCV, 2018.

RECKONING is a bi-level learning algorithm that improves language models' reasoning ability by folding contextual knowledge into parametric knowledge through back-propagation.

[ECAI 2024] A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization

This repository contains the source code used in the computational experiments of the paper: Learning to Solve Bilevel Programs with Binary Tender (ICLR 2024, available on OpenReview.net).

In this repository, we implement Targeted Meta-Learning (or Targeted Data-driven Regularization) architecture for training machine learning models with biased data.

Code accompanying the paper "Heuristic Methods for Gamma-Robust Mixed-Integer Linear Bilevel Problems" (with Ivana Ljubic and Martin Schmidt)

A program for generating computational results for a research project of mine involving a trilevel network interdiction game on an interdependent network.

Method of Adaptive Inexact Descent (MAID) for Bilevel Learning