A library for differentiable nonlinear optimization
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Updated
Jan 16, 2025 - 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
【ICMEW 2021】 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
Coresets via Bilevel Optimization
Implementation and examples from Trajectory Optimization with Optimization-Based Dynamics https://arxiv.org/abs/2109.04928
Benchmark for bi-level optimization solvers
PyTorch implementation of "STNs" and "Delta-STNs".
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)
Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"
JuMP-based toolbox for solving bilevel optimization problems
Solve optimization problems and build custom algorithms
PowerBiMIP is an open-source, efficient bilevel mixed-integer programming (BiMIP) solver, with a special focus on applications in power and energy systems.
Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO
Proposed a mathematical model for optimizing the profits and emissions while setting dynamic prices of electricity. A bilevel & multi-objective model is proposed for maximizing profits of retailer, minimizing the emissions produced, & minimizing the total cost of customers.
MetaOpt: Towards efficient heuristic design with quantifiable and confident performance
Example Code for paper "Provably Faster Algorithms for Bilevel Optimization"
Extended Mathematical Programming in Julia
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