Bryan Lim

CoRR, 2024

Evolutionary Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Enhancing MAP-Elites with Multiple Parallel Evolution Strategies.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms.

[BibT_eX]

[DOI]

Konstantinos I. Chatzilygeroudis

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity.

[BibT_eX]

[DOI]

Maxime Allard

Simón C. Smith

ACM Trans. Evol. Learn. Optim., June, 2023

Accelerated Quality-Diversity through Massive Parallelism.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Mix-ME: Quality-Diversity for Multi-Agent Learning.

[BibT_eX]

[DOI]

CoRR, 2023

QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration.

[BibT_eX]

[DOI]

CoRR, 2023

Multiple Hands Make Light Work: Enhancing Quality and Diversity using MAP-Elites with Multiple Parallel Evolution Strategies.

[BibT_eX]

[DOI]

CoRR, 2023

Efficient Learning of Locomotion Skills through the Discovery of Diverse Environmental Trajectory Generator Priors.

[BibT_eX]

[DOI]

Shikha Surana

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Efficient Exploration using Model-Based Quality-Diversity with Gradients.

[BibT_eX]

[DOI]

CoRR, 2022

Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Accelerated Quality-Diversity for Robotics through Massive Parallelism.

[BibT_eX]

[DOI]

CoRR, 2022

Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Learning to walk autonomously via reset-free quality-diversity.

[BibT_eX]

[DOI]

Alexander Reichenbach

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

QDax: on the benefits of massive parallelization for quality-diversity.

[BibT_eX]

[DOI]

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021

Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures.

[BibT_eX]

[DOI]

CoRR, 2021

Deep Learning for Market by Order Data.

[BibT_eX]

[DOI]

Zihao Zhang

CoRR, 2021

2020

Deep learning for time series prediction and decision making over time.

[BibT_eX]

[DOI]

PhD thesis, 2020

Building Cross-Sectional Systematic Strategies By Learning to Rank.

[BibT_eX]

[DOI]

CoRR, 2020

Time Series Forecasting With Deep Learning: A Survey.

[BibT_eX]

[DOI]

CoRR, 2020

Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio.

[BibT_eX]

[DOI]

Stephen Roberts

CoRR, 2020

Robust Autonomous Navigation of a Small-Scale Quadruped Robot in Real-World Environments.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction.

[BibT_eX]

[DOI]

Stephen Roberts

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Vision Aided Dynamic Exploration of Unstructured Terrain with a Small-Scale Quadruped Robot.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Tactile Object Pose Estimation from the First Touch with Geometric Contact Rendering.

[BibT_eX]

[DOI]

Maria Bauzá Villalonga

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting.

[BibT_eX]

[DOI]

CoRR, 2019

Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs.

[BibT_eX]

[DOI]

Stephen J. Roberts

CoRR, 2019

Enhancing Time Series Momentum Strategies Using Deep Neural Networks.

[BibT_eX]

[DOI]

Stephen J. Roberts

CoRR, 2019

2018

Forecasting Disease Trajectories in Alzheimer's Disease Using Deep Learning.

[BibT_eX]

[DOI]

Mihaela van der Schaar

CoRR, 2018

Disease-Atlas: Navigating Disease Trajectories with Deep Learning.

[BibT_eX]

[DOI]

Mihaela van der Schaar

CoRR, 2018

Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Disease-Atlas: Navigating Disease Trajectories using Deep Learning.

[BibT_eX]

[DOI]