NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
A fully decentralized hyperparameter optimization framework
Python library for stochastic numerical optimization
The official repo for GECCO 2022 paper High-Performance Evolutionary Algorithms for Online Neuronal Control in vivo and in silico
StochANNPy (STOCHAstic Artificial Neural Network for PYthon) provides user-friendly routines compatible with Scikit-Learn for stochastic learning.
Distributed surrogate-assisted evolutionary methods for multi-objective optimization of high-dimensional dynamical systems
StochOPy WebApp is hosted online at
This github repository contains the official code for the papers, "Robustness Assessment for Adversarial Machine Learning: Problems, Solutions and a Survey of Current Neural Networks and Defenses" and "One Pixel Attack for Fooling Deep Neural Networks"
Bandit and Evolutionary Algorithms using Python
Self-Interpretable Agent implemented on the Procgen game 'Dodgeball'.
Python framework for black-box optimization.
Three implemented evolutionary strategies using DEAP to optimize energy scheduling tasks.
All code for the results and figures shown in the report for the course AE4350.
Solving tough CEC-2017 composites.
Testing CMA_ESes and DEs on BBOB2009, CEC2017, and CEC2022.
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