NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
#计算机科学#A PyTorch Library for Multi-Task Learning
Evolutionary multi-objective optimization platform
A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
#计算机科学#Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
#计算机科学#🛍 A real-world e-commerce dataset for session-based recommender systems research.
High-performance metaheuristics for optimization coded purely in Julia.
Jupyter/IPython notebooks about evolutionary computation.
#计算机科学#Library for Jacobian descent with PyTorch. It enables optimization of neural networks with multiple losses (e.g. multi-task learning).
#计算机科学#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
#计算机科学#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.
#计算机科学#This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).
Multi-objective Bayesian optimization
Generalized and Efficient Blackbox Optimization System.
OptFrame - C++17/C++20/C++23 Optimization Framework in Single or Multi-Objective. Supports classic metaheuristics and hyperheuristics: Genetic Algorithm, Simulated Annealing, Tabu Search, Iterated Loc...