G
Greg Wayne
Researcher at Google
Publications - 45
Citations - 8657
Greg Wayne is an academic researcher from Google. The author has contributed to research in topics: Artificial neural network & Reinforcement learning. The author has an hindex of 26, co-authored 45 publications receiving 7065 citations.
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Neural Turing Machines
TL;DR: A combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-toend, allowing it to be efficiently trained with gradient descent.
Journal ArticleDOI
Hybrid computing using a neural network with dynamic external memory
Alex Graves,Greg Wayne,Malcolm Reynolds,Tim Harley,Ivo Danihelka,Agnieszka Grabska-Barwinska,Sergio Gomez Colmenarejo,Edward Grefenstette,Tiago Ramalho,John P. Agapiou,Adrià Puigdomènech Badia,Karl Moritz Hermann,Yori Zwols,Georg Ostrovski,Adam Cain,Helen King,Christopher Summerfield,Phil Blunsom,Koray Kavukcuoglu,Demis Hassabis +19 more
TL;DR: A machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer.
Posted Content
Neural Turing Machines
TL;DR: Neural Turing Machines as discussed by the authors extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes, analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end.
Posted Content
Emergence of Locomotion Behaviours in Rich Environments
Nicolas Heess,Dhruva Tb,Srinivasan Sriram,Jay Lemmon,Josh Merel,Greg Wayne,Yuval Tassa,Tom Erez,Ziyu Wang,S. M. Ali Eslami,Martin Riedmiller,David Silver +11 more
TL;DR: This paper explores how a rich environment can help to promote the learning of complex behavior, and finds that this encourages the emergence of robust behaviours that perform well across a suite of tasks.
Journal ArticleDOI
Vector-based navigation using grid-like representations in artificial agents
Andrea Banino,Caswell Barry,Benigno Uria,Charles Blundell,Timothy P. Lillicrap,Piotr Mirowski,Alexander Pritzel,Martin J. Chadwick,Thomas Degris,Joseph Modayil,Greg Wayne,Hubert Soyer,Fabio Viola,Brian Hu Zhang,Ross Goroshin,Neil C. Rabinowitz,Razvan Pascanu,Charles Beattie,Stig Petersen,Amir Sadik,Stephen Gaffney,Helen King,Koray Kavukcuoglu,Demis Hassabis,Raia Hadsell,Dharshan Kumaran +25 more
TL;DR: These findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation, and support neuroscientific theories that see grid cells as critical for vector-based navigation.