Wayne, Greg

Hybrid computing using a neural network with dynamic external memory

Graves, A., Wayne, G., Reynolds, M., Harley, T., Danihelka, I., Grabska-Barwińska, A., Colmenarejo, S. G., Grefenstette, E., Ramalho, T., Agapiou, J., et al. (2016) · Nature

Neural Networks and ApplicationsTopic Modeling

Cited by 1,412

Neural Turing Machines

Graves, A., Wayne, G., & Danihelka, I. (2014) · arXiv

Neural Networks and ApplicationsNeural Networks and Reservoir Computing

Cited by 1,058

A deep learning framework for neuroscience

Richards, B. A., Lillicrap, T. P., Beaudoin, P., Bengio, Y., Bogacz, R., Christensen, A., Clopath, C., Costa, R. P., de Berker, A., Ganguli, S., et al. (2019) · Nature Neuroscience

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 1,027

Emergence of Locomotion Behaviours in Rich Environments

Heess, N., TB, D., Sriram, S., Lemmon, J., Merel, J., Wayne, G., Tassa, Y., Erez, T., Wang, Z., Eslami, S. M. A., et al. (2017) · arXiv

Reinforcement Learning in RoboticsRobotic Locomotion and Control

Cited by 657

Experience Replay for Continual Learning

Rolnick, D., Ahuja, A., Schwarz, J., Lillicrap, T. P., & Wayne, G. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 529

Hierarchical motor control in mammals and machines

Merel, J., Botvinick, M., & Wayne, G. (2019) · Nature Communications

Reinforcement Learning in RoboticsMotor Control and Adaptation

Cited by 274

Toward an integration of deep learning and neuroscience

Marblestone, A. H., Wayne, G., & Kording, K. P. (2016) · Frontiers in Computational Neuroscience

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 119

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes

Rae, J. W., Hunt, J. J., Harley, T., Danihelka, I., Senior, A., Wayne, G., Graves, A., & Lillicrap, T. P. (2016) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 89

Optimizing Agent Behavior over Long Time Scales by Transporting Value

Hung, C.-C., Lillicrap, T., Abramson, J., Wu, Y., Mirza, M., Carnevale, F., Ahuja, A., & Wayne, G. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 75

A virtual rodent predicts the structure of neural activity across behaviours

Aldarondo, D., Merel, J., Marshall, J. D., Hasenclever, L., Klibaite, U., Gellis, A., Tassa, Y., Wayne, G., Botvinick, M., & Ölveczky, B. P. (2024) · Nature

Motor Control and AdaptationNeural dynamics and brain function

Cited by 70

Deep neuroethology of a virtual rodent

Merel, J., Aldarondo, D., Marshall, J., Tassa, Y., Wayne, G., & Ölveczky, B. (2019) · arXiv

Reinforcement Learning in RoboticsMotor Control and Adaptation

Cited by 44

Imitating Interactive Intelligence

Abramson, J., Ahuja, A., Barr, I., Brussee, A., Carnevale, F., Cassin, M., Chhaparia, R., Clark, S., Damoc, B., Dudzik, A., et al. (2020) · arXiv

Reinforcement Learning in RoboticsSocial Robot Interaction and HRI

Cited by 43

Hierarchical control using networks trained with higher-level forward models

Wayne, G., & Abbott, L. F. (2014) · Neural Computation

Reinforcement Learning in RoboticsNeural Networks and Applications

Cited by 14

Synthetic Returns for Long-Term Credit Assignment

Raposo, D., Ritter, S., Santoro, A., Wayne, G., Weber, T., Botvinick, M., van Hasselt, H., & Song, F. (2021) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 12