Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces

Constrained optimization toolkit for PyTorch

Towards Generalized and Efficient Blackbox Optimization System/Package (KDD 2021 & JMLR 2024)

A curated collection of Python examples for optimization-based solid simulation, emphasizing algorithmic convergence, penetration-free, and inversion-free conditions, designed for readability and understanding.

A general-purpose, deep learning-first library for constrained optimization in PyTorch

Unified knowledge-driven network inference from omics data

Generalized and Efficient Blackbox Optimization System.

An interior-point method written in python for solving constrained and unconstrained nonlinear optimization problems.

A Python Library for modeling combinatorial constrained problems

Library for Multi-objective optimization in Gradient Boosted Trees

Safe Pontryagin Differentiable Programming (Safe PDP) is a new theoretical and algorithmic safe differentiable framework to solve a broad class of safety-critical learning and control tasks.

The Modified Differential Multiplier Method (MDMM) for PyTorch

A dependency free library of standardized optimization test functions written in pure Python.

Synchronizing pong to music

PyTorch implementation of Constrained Policy Optimization

Python library to implement advanced trading strategies using machine learning and perform backtesting.

LAMBDA is a model-based reinforcement learning agent that uses Bayesian world models for safe policy optimization

Constrained optimization for Pytorch using the SQP-GS algorithm

A SciPy compatible super fast Python implementation for Particle Swarm Optimization.