Greg Wayne
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Artificial Intelligence top 2%
- Reinforcement Learning in Robotics
- Topic Modeling
- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Reservoir Computing
Papers in
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- Reinforcement Learning in Robotics 2
- Neural Networks and Applications 2
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- Advanced Memory and Neural Computing 6
- Ferroelectric and Negative Capacitance Devices 2
- Co-authors
- Adam Marblestone (2 shared papers)Konrad P. Körding (2 shared papers)Alex Graves (4 shared papers)Ivo Danihelka (4 shared papers)Josh Merel (5 shared papers)Matthew Botvinick (2 shared papers)Tim Harley (2 shared papers)Phil Blunsom (1 shared paper)
- Journals
- Nature (2 papers)Nature Communications (1 paper)Nature Neuroscience (1 paper)ACM Transactions on Graphics (1 paper)Neuron (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Greg Wayne
16 papers receiving 1.7k citations
Greg Wayne's Hit Papers
Peers
Comparison fields: 5 of 145
- Cognitive Neuroscience 502
- Artificial Intelligence 821
- Computer Vision and Pattern Recognition 342
- Neurology 75
- Sensory Systems 42
Countries citing papers authored by Greg Wayne
This map shows the geographic impact of Greg Wayne's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Greg Wayne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Wayne more than expected).
Fields of papers citing papers by Greg Wayne
This network shows the impact of papers produced by Greg Wayne. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Greg Wayne. The network helps show where Greg Wayne may publish in the future.
Co-authors
The 25 scholars most cited alongside Greg Wayne, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Hybrid computing using a neural network with dynamic external memory Hit paper breakdown → | 2016 | 699 |
| 2 | Toward an Integration of Deep Learning and Neuroscience Hit paper breakdown → | 2016 | 363 |
| 3 | 2019 | 150 | |
| 4 | 2014 | 115 | |
| 5 | Learning continuous control policies by stochastic value gradients | 2015 | 114 |
| 6 | 2020 | 60 | |
| 7 | 2014 | 54 | |
| 8 | 2016 | 52 | |
| 9 | 2023 | 28 | |
| 10 | 2024 | 27 | |
| 11 | Robust imitation of diverse behaviors | 2017 | 25 |
| 12 | 2016 | 24 | |
| 13 | 2016 | 15 | |
| 14 | Hierarchical Visuomotor Control of Humanoids. | 2018 | 10 |
| 15 | 2011 | 5 | |
| 16 | 2014 | 5 |
About Greg Wayne
Greg Wayne is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Control and Systems Engineering, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 1.7k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Neural dynamics and brain function (4 papers), Robot Manipulation and Learning (4 papers), Ferroelectric and Negative Capacitance Devices (2 papers), Human Motion and Animation (2 papers), Reinforcement Learning in Robotics (2 papers), Human Pose and Action Recognition (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Cognitive Neuroscience (502 citations), Artificial Intelligence (821 citations), Computer Vision and Pattern Recognition (342 citations), Neurology (75 citations) and Sensory Systems (42 citations). Greg Wayne has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Adam Marblestone, Konrad P. Körding, Alex Graves, Ivo Danihelka, Josh Merel, Matthew Botvinick, Tim Harley, Phil Blunsom, John Agapiou and Tiago Ramalho. Their work appears in journals such as Nature, Nature Communications, Nature Neuroscience, ACM Transactions on Graphics and Neuron.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.