Neil C. Rabinowitz
- Artificial Intelligence top 0.2%
- Computer Vision and Pattern Recognition top 0.5%
- Cognitive Neuroscience top 2%
- Electrical and Electronic Engineering top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Co-authors
- Demis HassabisDharshan KumaranRaia HadsellAgnieszka Grabska‐BarwińskaTiago RamalhoClaudia ClopathRazvan PascanuKieran Milan
- Topics
- Neural dynamics and brain function (6 papers)Visual perception and processing mechanisms (3 papers)Reinforcement Learning in Robotics (3 papers)
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
Neil C. Rabinowitz
14 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Artificial Intelligence 3.0k
- Computer Vision and Pattern Recognition 1.6k
- Cognitive Neuroscience 733
- Electrical and Electronic Engineering 314
- Radiology, Nuclear Medicine and Imaging 248
Countries citing papers authored by Neil C. Rabinowitz
This map shows the geographic impact of Neil C. Rabinowitz'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 Neil C. Rabinowitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil C. Rabinowitz more than expected).
Fields of papers citing papers by Neil C. Rabinowitz
This network shows the impact of papers produced by Neil C. Rabinowitz. 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 Neil C. Rabinowitz. The network helps show where Neil C. Rabinowitz may publish in the future.
Co-authorship network of co-authors of Neil C. Rabinowitz
This figure shows the co-authorship network connecting the top 25 collaborators of Neil C. Rabinowitz. A scholar is included among the top collaborators of Neil C. Rabinowitz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Neil C. Rabinowitz. Neil C. Rabinowitz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | Human-level performance in 3D multiplayer games with population-based reinforcement learningbreakdown → | 349 |
| 3 | Relational Forward Models for Multi-Agent Learning | 7 |
| 4 | On the importance of single directions for generalization | 15 |
| 5 | 27 | |
| 6 | Learned Deformation Stability in Convolutional Neural Networks. | 6 |
| 7 | The predictron: end-to-end learning and planning | 25 |
| 8 | Overcoming catastrophic forgetting in neural networksbreakdown → | 3594 |
| 9 | 120 | |
| 10 | 103 | |
| 11 | 55 | |
| 12 | 3 | |
| 13 | 183 | |
| 14 | 65 |
About Neil C. Rabinowitz
Neil C. Rabinowitz is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Sensory Systems, having authored 14 papers that have together received 4.6k indexed citations. Recurring topics across this work include Neural dynamics and brain function (6 papers), Visual perception and processing mechanisms (3 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Artificial Intelligence (3.0k citations), Computer Vision and Pattern Recognition (1.6k citations) and Cognitive Neuroscience (733 citations). Neil C. Rabinowitz has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Demis Hassabis, Dharshan Kumaran, Raia Hadsell, Agnieszka Grabska‐Barwińska, Tiago Ramalho, Claudia Clopath, Razvan Pascanu, Kieran Milan, James Kirkpatrick and Guillaume Desjardins. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.
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.