Roberts, Stephen

Deep Reinforcement Learning for Trading

Zhang, Z., Zohren, S., & Roberts, S. (2020) · The Journal of Financial Data Science

Stock Market Forecasting MethodsFinancial Markets and Investment Strategies

Cited by 227

Inferring social network structure in ecological systems from spatio-temporal data streams

Psorakis, I., Roberts, S. J., Rezek, I., & Sheldon, B. C. (2012) · Journal of The Royal Society Interface

Complex Network Analysis TechniquesAnimal Behavior and Reproduction

Cited by 171

Variational Bayes for generalized autoregressive models

Roberts, S. J., & Penny, W. D. (2002) · IEEE Transactions on Signal Processing

Bayesian Methods and Mixture ModelsControl Systems and Identification

Cited by 157

Inferring social structure from temporal data

Psorakis, I., Voelkl, B., Garroway, C. J., Radersma, R., Aplin, L. M., Crates, R. A., Culina, A., Farine, D. R., Firth, J. A., Hinde, C. A., et al. (2015) · Behavioral Ecology and Sociobiology

Animal Behavior and ReproductionAvian ecology and behavior

Cited by 95

Effective Diversity in Population-Based Reinforcement Learning

Parker-Holder, J., Pacchiano, A., Choromanski, K., & Roberts, S. (2020) · arXiv

Reinforcement Learning in RoboticsEvolutionary Algorithms and Applications

Cited by 60

Quantum algorithms for training Gaussian processes

Zhao, Z., Fitzsimons, J. K., Osborne, M. A., Roberts, S. J., & Fitzsimons, J. F. (2019) · Physical Review A

Quantum Computing Algorithms and ArchitectureGaussian Processes and Bayesian Inference

Cited by 19

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Ball, P. J., Lu, C., Parker-Holder, J., & Roberts, S. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 11