NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
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Updated
Jul 7, 2026 - Python
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
A PyTorch Library for Multi-Task Learning
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Towards Generalized and Efficient Blackbox Optimization System/Package (KDD 2021 & JMLR 2024)
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning).
🛍 A real-world e-commerce dataset for session-based recommender systems research.
Deep learning toolkit for Drug Design with Pareto-based Multi-Objective optimization in Polypharmacology
Deep Reinforcement Learning for Multiobjective Optimization. Code for this paper
[ECCV2020] NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search
Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.
AutoOED: Automated Optimal Experimental Design Platform
Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.
Multi-objective Bayesian optimization
Generalized and Efficient Blackbox Optimization System.
Library for Multi-objective optimization in Gradient Boosted Trees
A Universal Deep Reinforcement Learning Framework
Exact Pareto Optimal solutions for preference based Multi-Objective Optimization
[ICLR 2025] The offical implementation of "PSEC: Skill Expansion and Composition in Parameter Space", a new framework designed to facilitate efficient and flexible skill expansion and composition, iteratively evolve the agents' capabilities and efficiently address new challenges
This is my implementation of a branch and price algorithm to solve the humanitarian aid distribution problem. This problem is a VRP with a specific objective function
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