Python library for CMA Evolution Strategy.
hyperparameter-optimization black-box-optimization evolution-strategy evolution-strategies cma-es optuna
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Feb 10, 2026 - Python
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cma-es
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A bare-bones Python library for quality diversity optimization.
python deep-learning optimization openai-gym artificial-intelligence evolutionary-algorithms evolutionary-computation quality-diversity cma-es map-elites llms
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Mar 12, 2026 - Python
Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)
pytorch generative-adversarial-network pretrained-models cma-es latent-space augmented-lagrangian-method layoutgan
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Jul 24, 2023 - Python
Distributed implementation of popular evolutionary methods
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Dec 26, 2017 - Python
Yarpiz Evolutionary Algorithms Toolbox for MATLAB
optimization genetic-algorithm simulated-annealing ant-colony-optimization differential-evolution evolutionary-computation optimization-algorithms particle-swarm-optimization firefly-algorithm metaheuristics harmony-search evolution-strategies artificial-bee-colony bees-algorithm cma-es imperialistic-competitive-algorithm tlbo covariance-matrix-adaptation biogeography-based-optimization invasive-weed-optimization
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Dec 15, 2020 - HTML
(GECCO 2022) CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization
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Mar 20, 2024 - Python
A julia implementation of the CMA Evolution Strategy for derivative-free optimization of potentially non-linear, non-convex or noisy functions over continuous domains.
optimization evolutionary-algorithm evolutionary-strategy stochastic-optimization derivative-free blackbox-optimization cma-es derivative-free-optimization
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Jan 3, 2023 - Julia
Official implementation of paper "BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement".
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Dec 19, 2025 - Python
Official implementation of "Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning"
deep-learning optimization openai-gym artificial-intelligence evolutionary-algorithms evolutionary-computation quality-diversity cma-es map-elites
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Oct 3, 2022 - Python
(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems
black-box-optimization evolution-strategy evolution-strategies natural-gradients cma-es natural-evolution-strategies
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Nov 16, 2023 - Python
Genetic algorithms and CMA-ES (covariance matrix adaptation evolution strategy) for efficient feature selection
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Aug 11, 2025 - Jupyter Notebook
CMA-ES in MATLAB
optimization evolutionary-algorithms evolutionary-algorithm evolutionary-computation cma evolution-strategy cmaes evolution-strategies cma-es estimation-of-distribution covariance-matrix-adaptation evolution-of-evolution
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Dec 5, 2020 - MATLAB
Covariance Matrix Adaptation Evolution Strategy (CMA-ES) implementation on C#
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May 12, 2024 - C#
Modern PyTorch implementation of World Models with interactive notebooks for the Car Racing environment. Features VAE vision model, MDN-RNN memory system, and CMA-ES controller with visualization tools. Complete end-to-end reinforcement learning pipeline with clean, well-documented code.
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May 5, 2025 - Jupyter Notebook
Deep learning and evolutionary algorithms for identification of aerodynamic parameters
deep-learning lstm gru rnn evolutionary-algorithms system-identification aerodynamics dynamic-modelling cma-es
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Sep 19, 2021 - Python
High-performance Echo State Network simulation, optimization and visualization in modern C++.
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Apr 12, 2025 - C++
Reproduce the results of "Neuroevolution of Self-Interpretable Agents" paper
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Sep 22, 2023 - Python
[TMLR'26] PriSM: Prior-Guided Search Methods for Query Efficient Black-Box Adversarial Attacks
machine-learning thesis genetic-algorithm evolutionary-algorithms publication query-optimization saliency-map robustness adversarial-machine-learning adversarial-examples cma-es adversarial-attacks bsc-thesis adversarial-robustness square-attack transfer-based-attacks tmlr machine-learning-robustness tmlr-2026
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Mar 18, 2026 - Python
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).
machine-learning neural-network robotics artificial-intelligence experimentation evolutionary-computation evolutionary-robotics webots novelty-search cma-es map-elites deap-library
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Apr 4, 2021 - Python
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