awesome-deep-neuroevolution
A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)
https://github.com/Alro10/awesome-deep-neuroevolution
Last synced: 4 days ago
JSON representation
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Papers
- An adaptive neuroevolution-based hyperheuristic
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- EVOLUTIONARY POPULATION CURRICULUM FOR SCALING MULTI-AGENT REINFORCEMENT LEARNING
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVs
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Towards continual reinforcement learning through evolutionary meta-learning
- Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies
- Meta-Learning in Neural Networks: A Survey
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- PBCS: Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Exploring the evolution of GANs through quality diversity
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Learning and Implementing Deep Learning Methods
- Generating CNNs using Genetic Algorithm
- A Neuroevolutionary Approach to Evolve a Flexible Neural Controller for a Morphology Changing Quadruped Robot - Wonho Lee | not yet | 2020 |
- Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search
- CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices
- Using Deep Neuroevolution to train Deep Reinforcement Learning Agents
- Analyzing the Components of Distributed Coevolutionary GAN Training - group/lipizzaner-gan)] | 2020 |
- Developmental neuronal networks as models to study the evolution of biological intelligence
- CoNES: Convex Natural Evolutionary Strategies - lab/conES)]| 2020 |
- One-Shot Neural Architecture Search via Novelty Driven Sampling - 20 |
- Coevolutionary Learning of Neuromodulated Controllers for Multi-Stage and Gamified Tasks
- Online NEAT for Credit Evaluation - a Dynamic Problem with Sequential Data
- Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies
- NEUROEVOLUTIONARY TRANSFER LEARNING OF DEEP RECURRENT NEURAL NETWORKS THROUGH NETWORK-AWARE ADAPTATION
- Combining a gradient-based method and an evolution strategy for multi-objective reinforcement learning
- Efficient Architecture Search for Deep Neural Networks
- Evolutionary Automation of Coordinated Autonomous Vehicles
- Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search
- TRAINING ADAPTABLE NEURAL NETWORKS BASED ON EVOLVABILITY SEARCH
- IMPROVING NEUROEVOLUTION USING ISLAND EXTINCTION AND REPOPULATION
- Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
- Novelty Search makes Evolvability Inevitable
- Genetic Deep Reinforcement Learning for Mapless Navigation
- Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems
- A Hybrid Method for Training Convolutional Neural Networks
- An Effective Maximum Entropy Exploration Approach for Deceptive Game in Reinforcement Learning
- First return then explore - research/go-explore)] | 2020 |
- Neuromodulated multiobjective evolutionary neurocontrollers without speciation
- PBCS: Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning
- Efficient Evolutionary Neural Architecture Search (NAS) by Modular Inheritable Crossover - TA 2020 |
- Diversity Preservation in Minimal Criterion Coevolution through Resource Limitation
- Meta-Learning in Neural Networks: A Survey
- Improving Deep Reinforcement Learning with Advanced Exploration and Transfer Learning Techniques
- Using Skill Rating as Fitness on the Evolution of GANs
- ModuleNet: Knowledge-inherited Neural Architecture Search
- The Expense of Neuro-Morpho Functional Machines
- Evolutionary recurrent neural network for image captioning
- Learning Stabilizing Control Policies for a Tensegrity Hopper with Augmented Random Search
- Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution
- Incremental Evolution and Development of Deep Artificial Neural Networks - denser3) | 2020 |
- Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks
- Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods
- EVOLUTIONARY POPULATION CURRICULUM FOR SCALING MULTI-AGENT REINFORCEMENT LEARNING
- Optimisation of Phonetic Aware Speech Recognition through Multi-objective Evolutionary Algorithms - systems-with-applications) |
- A Brain-Inspired Framework for Evolutionary Artificial General Intelligence - Tehrani, et al. | not yet | 2020 |
- The use of Genetic Programming for detecting the incorrect predictions of Classification Models
- Hyper-Parameter Selection in Convolutional Neural Networks Using Microcanonical Optimization Algorithm
- Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
- Neuroevolution of Self-Interpretable Agents
- META-LEARNING CURIOSITY ALGORITHMS - learning-curiosity-algorithms) | **ICLR 2020** |
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Action Unit Analysis Enhanced Facial Expression Recognition by Deep Neural Network Evolution
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVs
- EGAD! an Evolved Grasping Analysis Dataset for diversity and reproducibility in robotic manipulation - blog](https://dougsm.github.io/egad/) | 2020 |
- Scaling MAP-Elites to Deep Neuroevolution
- Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
- AN EVOLUTIONARY DEEP LEARNING METHOD FOR SHORT-TERM WIND SPEED PREDICTION: A CASE STUDY OF THE LILLGRUND OFFSHORE WIND FARM
- Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription
- Highly Efficient Deep Intelligence via Multi-Parent Evolutionary Synthesis of Deep Neural Networks
- NEUROEVOLUTION OF NEURAL NETWORK ARCHITECTURES USING CODEEPNEAT AND KERAS - CoDeepNEAT) | 2020 |
- Horizontal gene transfer for recombining graphs - plasma/EGGP) | Genetic Programming and Evolvable Machines (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Improving the Performance of Evolutionary Algorithms via Gradient-Based Initialization
- Evolving Loss Functions With Multivariate Taylor Polynomial Parameterizations
- Evolving Neural Networks through a Reverse Encoding Tree
- Evolutionary LSTM-FCN networks for pattern classification in industrial processes
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Hierarchy and co-evolution processes in urban systems
- A Study of Fitness Landscapes for Neuroevolution
- Combining Evolution and Learning in Computational Ecosystems
- Examining Hyperparameters of Neural Networks Trained Using Local Search
- Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
- POPULATION-GUIDED PARALLEL POLICY SEARCH FOR REINFORCEMENT LEARNING
- IMPROVING DEEP NEUROEVOLUTION VIA DEEP INNOVATION PROTECTION - research/ga-world-models/) | 2020 |
- AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence
- Differential Evolution for Neural Networks Optimization
- Neuro-Evolution Search Methodologies for Collective Self-Driving Vehicles - Lun (Allen) Huang | Master thesis | 2019 |
- Using Neuroevolved Binary Neural Networks to solve reinforcement learning environments
- Neuroevolution with CMA-ES for Real-time Gain Tuning of a Car-like Robot Controller
- Learning to grow: control of materials self-assembly using evolutionary reinforcement learning
- Network of Evolvable Neural Units: Evolving to Learn at a Synaptic Level
- GENERATIVE TEACHING NETWORKS: ACCELERATING NEURAL ARCHITECTURE SEARCH BY LEARNING TO GENERATE SYNTHETIC TRAINING DATA
- Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization
- GAIM: A C++ library for Genetic Algorithms and Island Models
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Automatic Design of Convolutional Neural Networks using Grammatical Evolution
- Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency
- An Evolutionary Approach to Compact DAG Neural Network Optimization
- Multi-Criterion Evolutionary Design of Deep Convolutional Neural Networks - net)] | 2019 |
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- A Graph-Based Encoding for Evolutionary Convolutional Neural Network Architecture Design - Harris, et al. | not yet | 2019 IEEE Congress on Evolutionary Computation (CEC) |
- Auto-creation of Effective Neural Network Architecture by Evolutionary Algorithm and ResNet for Image Classification
- Evolving Knowledge And Structure Through Evolution-based Neural Architecture Search
- Culturally Evolved GANs for generating Fake Stroke Faces
- Neuroevolutionary Training of Deep Convolutional Generative Adversarial Networks
- UMA ESTRUTURA PARA EXECUCAO DE REDES NEURAIS EVOLUTIVAS NA GPU
- An Overview of Open-Ended Evolution: Editorial Introduction to the Open-Ended Evolution II Special Issue
- Deep neural network architecture search using network morphism
- Neuroevolutive Algorithms for Learning Gaits in Legged Robots
- Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control
- Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling - Chang Lee, et al. | [repo](https://github.com/logue311/EDNAS) | 2019 |
- ES-MAML: Simple Hessian-Free Meta Learning
- Empirical study on the performance of Neuro Evolution of Augmenting Topologies (NEAT) - driving) | 2019 |
- Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions
- Algebraic Neural Architecture Representation, Evolutionary Neural Architecture Search, and Novelty Search in Deep Reinforcement Learning
- GACNN: TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS WITH GENETIC ALGORITHM
- Implicit Multi-Objective Coevolutionary Algorithms
- CEM-RL: Combining evolutionary and gradient-based methods for policy search - RL) | ICLR 2019 |
- Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution
- Exploring Randomly Wired Neural Networks for Image Recognition
- Designing neural networks through neuroevolution
- Guided evolutionary strategies: escaping the curse of dimensionality in random search - Dickstein| [repo](https://github.com/brain-research/guided-evolutionary-strategies)  | ICML 2019|
- Collaborative Evolutionary Reinforcement Learning - evolutionary-reinforcement-learning) | ICML 2019 |
- Trust Region Evolution Strategies
- Deep Neuroevolution of Recurrent and Discrete World Models - world-models) | 2019 |
- Proximal Distilled Evolutionary Reinforcement Learning
- POET: open-ended coevolution of environments and their optimized solutions
- COEGAN: evaluating the coevolution effect in generative adversarial networks
- Diverse Agents for Ad-Hoc Cooperation in Hanabi
- EPNAS: Efficient Progressive Neural Architecture Search
- Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition
- Fast DENSER: Efficient Deep NeuroEvolution - denser) | EuroGP 2019 |
- AlphaStar: An Evolutionary Computation Perspective
- Automatic Design of Artificial Neural Networks for Gamma-Ray Detection
- Evolvability ES: Scalable and Direct Optimization of Evolvability - research/Evolvability-ES) | GECCO 2019 |
- Automated Neural Network Construction with Similarity Sensitive Evolutionary Algorithms
- Provably Robust Blackbox Optimization for Reinforcement Learning
- Go-Explore: a New Approach for Hard-Exploration Problems
- Culturally Evolved GANs for Generating Fake Stroke Faces
- An Evolution Strategy with Progressive Episode Lengths for Playing Games
- On Hard Exploration for Reinforcement Learning: A Case Study in Pommerman - Leal, Matthew E. Taylor | not yet | 2019 |
- A Knee-Guided Evolutionary Algorithm for Compressing Deep Neural Networks
- Multi-task Deep Reinforcement Learning with Evolutionary Algorithm and Policy Gradients Method in 3D Control Tasks
- Evolutionary deep learning
- Guiding Evolutionary Strategies with Off-Policy Actor-Critic
- Construction of Macro Actions for Deep Reinforcement Learning - Hsiang Chang, Kuan-Yu Chang, Henry Kuo, Chun-Yi Lee | not yet | 2019 |
- Fast Automatic Optimisation of CNN Architectures for Image Classification Using Genetic Algorithm
- Memetic Evolution Strategy for Reinforcement Learning
- Epigenetic evolution of deep convolutional models
- A CROSS-DATA SET EVALUATION OF GENETICALLY EVOLVED NEURAL NETWORK ARCHITECTURES
- Architecture Search by Estimation of Network Structure Distributions
- Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- A Restart-based Rank-1 Evolution Strategy for Reinforcement Learning - 19 |
- Evolution of Kiting Behavior in a Two Player Combat Problem
- Learning to Select Mates in Evolving Non-playable Characters
- MULTI-SPECIES EVOLUTIONARY ALGORITHMS FOR COMPLEX OPTIMISATION PROBLEMS
- ATTRACTION-REPULSION ACTOR-CRITIC FOR CONTINUOUS CONTROL REINFORCEMENT LEARNING
- Comparative Study of Neuro-Evolution Algorithms in Reinforcement Learning for Self-Driving Cars
- An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution
- THE ANT SWARM NEURO-EVOLUTION PROCEDURE FOR OPTIMIZING RECURRENT NETWORKS
- Correlation Analysis-Based Neural Network Self-Organizing Genetic Evolutionary Algorithm
- Learning Task-specific Activation Functions using Genetic Programming
- A HYBRID NEURAL NETWORK AND GENETIC PROGRAMMING APPROACH TO THE AUTOMATIC CONSTRUCTION OF COMPUTER VISION SYSTEMS - Davidson | not | Master Thesis 2019 |
- Novelty Search for Deep Reinforcement Learning Policy Network Weights by Action Sequence Edit Metric Distance
- Playing Atari with Six Neurons - Mauroux | [[repo](https://github.com/giuse/DNE/tree/nips2018)]  | 2018, AAMAS 2019 |
- Simple random search provides a competitive approach to reinforcement learning
- Regularized Evolution for Image Classifier Architecture Search - research/google-research/blob/master/evolution/regularized_evolution_algorithm/regularized_evolution.ipynb) | 2018, AAAI 2019 |
- Evolution-Guided Policy Gradient in Reinforcement Learning
- Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
- Experimental Evaluation of Metaheuristic Optimization of Gradients as an Alternative to Backpropagation
- Evolution Strategies as a Scalable Alternative to Reinforcement Learning - strategies-starter)] [[blog](https://blog.openai.com/evolution-strategies/)] | 2017 |
- Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning - research/deep-neuroevolution)] [[blog](https://eng.uber.com/deep-neuroevolution/)]| 2017 |
- Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients - research/safemutations) | 2017 |
- Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents - research/deep-neuroevolution) | 2017, NIPS 2018 |
- On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent - neuroevolution/) | 2017 |
- ES Is More Than Just a Traditional Finite-Difference Approximator - neuroevolution/) | 2017 |
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Procedural Generation of Quests for Games Using Genetic Algorithms and Automated Planning
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- A Comparison of Evolutionary and Tree-Based Approaches for Game Feature Validation in RealTime Strategy Games with a Novel Metric
- Procedural Generation of Quests for Games Using Genetic Algorithms and Automated Planning
- Learning and Implementing Deep Learning Methods
- Learning feature spaces for regression with genetic programming
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning to walk - reward relevance within an enhanced neuroevolution approach
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices
- Analyzing the Components of Distributed Coevolutionary GAN Training - group/lipizzaner-gan)] | 2020 |
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- CoNES: Convex Natural Evolutionary Strategies - lab/conES)]| 2020 |
- Online NEAT for Credit Evaluation - a Dynamic Problem with Sequential Data
- Adversarial genetic programming for cyber security: a rising application domain where GP matters - May O’Reilly, et al. | not yet | Genetic Programming and Evolvable Machines 2020 |
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- An Evolutionary Approach to Compact DAG Neural Network Optimization
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Learning feature spaces for regression with genetic programming
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Culturally Evolved GANs for generating Fake Stroke Faces
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Neuro-Evolution Search Methodologies for Collective Self-Driving Vehicles - Lun (Allen) Huang | Master thesis | 2019 |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Coevolutionary Learning of Neuromodulated Controllers for Multi-Stage and Gamified Tasks
- Learning feature spaces for regression with genetic programming
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Examining Hyperparameters of Neural Networks Trained Using Local Search
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Coping with opponents: multi-objective evolutionary neural networks for fighting games - Nieberg | not yet | Neural Computing and Applications (2020) |
- Evolutionary music: applying evolutionary computation to the art of creating music
- Evolving deep neural networks using coevolutionary algorithms with multi-population strategy
- A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization - 981-15-0994-0) |
- Using Neuroevolution for Predicting Mobile Marketing Conversion
- Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Learning feature spaces for regression with genetic programming
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Learning feature spaces for regression with genetic programming
- Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer
- Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization - Pulido, et al. | not yet | OLA 2020 |
- Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks
- Evolving neural network agents to play atari games with compact state representations
- Improving neuroevolutionary transfer learning of deep recurrent neural networks through network-aware adaptation
- NEUROEVOLUTIONARY TRANSFER LEARNING OF DEEP RECURRENT NEURAL NETWORKS THROUGH NETWORK-AWARE ADAPTATION
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Tutorials
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
- Paper experiments replication: Deep Neuroevolution Uber
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Conferences
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Resources
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Researchers
- Kenneth O. Stanley - Uber AI Labs.
- Jeff Clune - Open AI.
- Risto Miikkulainen - University of Texas at Austin.
- Nuno Lourenço - University of Coimbra.
Categories
Sub Categories