Dylan Banarse
Impact in
- General Social Sciences top 10%
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- Neural Networks and Applications
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Reinforcement Learning in Robotics
- Machine Learning and Data Classification
Papers in ⓘ
-
- Image Processing and 3D Reconstruction 2
- Face and Expression Recognition 2
- Digital Imaging for Blood Diseases 1
- Co-authors
- A.W.G. Duller (5 shared papers)Chrisantha Fernando (3 shared papers)Marc Lanctot (1 shared paper)Frederic Besse (1 shared paper)Malcolm Reynolds (1 shared paper)David Pfau (1 shared paper)Max Jaderberg (1 shared paper)Daan Wierstra (1 shared paper)
- Journals
- Advances in Engineering Software (1 paper)Neural Computing and Applications (1 paper)Adaptive Behavior (1 paper)Neural Processing Letters (1 paper)UCL Discovery (University College London) (1 paper)
- Partner nations
- United KingdomCanada
In The Last Decade
Dylan Banarse
7 papers receiving 72 citations
Peers
Comparison fields: 5 of 36
- General Social Sciences 6
- Artificial Intelligence 55
- Human-Computer Interaction 9
- Computer Vision and Pattern Recognition 23
- Ecological Modeling 2
Countries citing papers authored by Dylan Banarse
This map shows the geographic impact of Dylan Banarse'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 Dylan Banarse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dylan Banarse more than expected).
Fields of papers citing papers by Dylan Banarse
This network shows the impact of papers produced by Dylan Banarse. 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 Dylan Banarse. The network helps show where Dylan Banarse may publish in the future.
Co-authors
The 15 scholars most cited alongside Dylan Banarse, 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 | 2016 | 44 | |
| 2 | 2000 | 10 | |
| 3 | 2002 | 8 | |
| 4 | 2019 | 6 | |
| 5 | 1997 | 5 | |
| 6 | 1997 | 2 | |
| 7 | 2024 | 1 | |
| 8 | Application of Neural Deformable Templates to Hand Written Digit Classification. | 1997 | 0 |
About Dylan Banarse
Dylan Banarse is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Biophysics, Artificial Intelligence and Cultural Studies, having authored 8 papers that have together received 76 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Image Processing and 3D Reconstruction (2 papers), Face and Expression Recognition (2 papers), Digital Imaging for Blood Diseases (1 paper), Cell Image Analysis Techniques (1 paper), Action Observation and Synchronization (1 paper), Evolutionary Algorithms and Applications (1 paper) and Advanced Algorithms and Applications (1 paper). The work is most often cited by research in General Social Sciences (6 citations), Artificial Intelligence (55 citations), Human-Computer Interaction (9 citations), Computer Vision and Pattern Recognition (23 citations) and Ecological Modeling (2 citations). Dylan Banarse has collaborated with scholars based in United Kingdom and Canada. Frequent co-authors include A.W.G. Duller, Chrisantha Fernando, Marc Lanctot, Frederic Besse, Malcolm Reynolds, David Pfau, Max Jaderberg, Daan Wierstra, Siqi Liu and Pushmeet Kohli. Their work appears in journals such as Advances in Engineering Software, Neural Computing and Applications, Adaptive Behavior, Neural Processing Letters and UCL Discovery (University College London).
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.