Python library for CMA Evolution Strategy.

A bare-bones Python library for quality diversity optimization.

Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)

Distributed implementation of popular evolutionary methods

Code for: Transforming and Projecting Images into Class-conditional Generative Networks

Official implementation of paper "BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement".

Deep learning and evolutionary algorithms for identification of aerodynamic parameters

Can LLMs beat classical HPO? A benchmark comparing classical, LLM-based, and hybrid methods on Karpathy's autoresearch.

(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems

(GECCO 2022) CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization

Reproduce the results of "Neuroevolution of Self-Interpretable Agents" paper

Convert images into low poly, using an optimizer

A new version of world models using Echo-state networks and random weight-fixed CNNs

Python codes for Assessment of thermal mode-based kinetic models via stratified cross-validation and TPE optimization

Python implementation of Regulated Evolution Strategies with Covariance Matrix Adaption for continuous "Black-Box" optimization problems.

Black Box Optimizers for Complex Systems

(EvoApps2022) "Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies"

A universal supervisor controller and ER suite for Webots that can be adapted to any wheeled robot morphology with ease. The project is also setup to allow for easy Reinforcement Learning experimentation with some select algorithms (CMA-ES, Novlty Search, MAP-Elites) and neural networks (fixed and recurrent).

Master project

This repository includes Python implementations of popular optimization algorithms, which can enhance project performance in solving complex problems.