Tim Harley
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- Reinforcement Learning in Robotics
- Neural Networks and Reservoir Computing
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- Multimodal Machine Learning Applications
Papers in
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- Neural Networks and Applications 2
- Domain Adaptation and Few-Shot Learning 2
- Explainable Artificial Intelligence (XAI) 2
- Topic Modeling 2
- Speech Recognition and Synthesis 1
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- Speech and Audio Processing 1
- Music and Audio Processing 1
- Co-authors
- Ivo DanihelkaGreg WayneAlex GravesSergio Gómez ColmenarejoMalcolm ReynoldsAdrià Puigdomènech BadiaGeorg OstrovskiYori Zwólš
- Journals
- Nature (1 paper)Ergonomics (1 paper)International Conference on Machine Learning (1 paper)arXiv (Cornell University) (1 paper)International Conference on Learning Representations (1 paper)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Tim Harley
7 papers receiving 752 citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Artificial Intelligence 510
- Computer Vision and Pattern Recognition 190
- Cognitive Neuroscience 92
- Computer Science Applications 22
- Computational Theory and Mathematics 61
Countries citing papers authored by Tim Harley
This map shows the geographic impact of Tim Harley'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 Tim Harley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Harley more than expected).
Fields of papers citing papers by Tim Harley
This network shows the impact of papers produced by Tim Harley. 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 Tim Harley. The network helps show where Tim Harley may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tim Harley, 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 | Multiplicative Interactions and Where to Find Them | 2020 | 20 |
| 2 | 2019 | 26 | |
| 3 | The predictron: end-to-end learning and planning | 2017 | 25 |
| 4 | Hybrid computing using a neural network with dynamic external memory Hit paper breakdown → | 2016 | 683 |
| 5 | 2016 | 25 | |
| 6 | There's more than one way. | 1982 | 1 |
| 7 | 1972 | 17 |
About Tim Harley
Tim Harley is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Infectious Diseases, having authored 7 papers that have together received 797 indexed citations. Recurring topics across this work include Neural Networks and Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Topic Modeling (2 papers), Speech Recognition and Synthesis (1 paper), Speech and Audio Processing (1 paper), Music and Audio Processing (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Artificial Intelligence (510 citations), Computer Vision and Pattern Recognition (190 citations), Cognitive Neuroscience (92 citations), Computer Science Applications (22 citations) and Computational Theory and Mathematics (61 citations). Tim Harley has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Ivo Danihelka, Greg Wayne, Alex Graves, Sergio Gómez Colmenarejo, Malcolm Reynolds, Adrià Puigdomènech Badia, Georg Ostrovski, Yori Zwólš, Agnieszka Grabska‐Barwińska and Demis Hassabis. Their work appears in journals such as Nature, Ergonomics, International Conference on Machine Learning, arXiv (Cornell University) and International Conference on Learning Representations.
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.