John Quan
Impact in
- Artificial Intelligence top 0.2%
- Domain Adaptation and Few-Shot Learning
- Reinforcement Learning in Robotics
- Machine Learning and ELM
- Topic Modeling
- Anomaly Detection Techniques and Applications
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Human Pose and Action Recognition
Papers in
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- Reinforcement Learning in Robotics 4
- Security and Verification in Computing 1
- Evolutionary Algorithms and Applications 1
- Domain Adaptation and Few-Shot Learning 1
- Explainable Artificial Intelligence (XAI) 1
- Semantic Web and Ontologies 1
- Co-authors
- Guillaume Desjardins (1 shared paper)Neil C. Rabinowitz (1 shared paper)Demis Hassabis (1 shared paper)Tiago Ramalho (1 shared paper)Andrei A. Rusu (1 shared paper)Agnieszka Grabska‐Barwińska (1 shared paper)Kieran Milan (1 shared paper)Clopath Claudia (1 shared paper)
- Journals
- IT Professional (1 paper)Proceedings of the National Academy of Sciences (1 paper)Lecture notes in computer science (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
John Quan
6 papers receiving 5.3k citations
John Quan's Hit Papers
Peers
Comparison fields: 5 of 151
- Artificial Intelligence 3.9k
- Computer Vision and Pattern Recognition 2.0k
- Health Informatics 43
- Signal Processing 211
- Control and Systems Engineering 433
Countries citing papers authored by John Quan
This map shows the geographic impact of John Quan'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 John Quan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Quan more than expected).
Fields of papers citing papers by John Quan
This network shows the impact of papers produced by John Quan. 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 John Quan. The network helps show where John Quan may publish in the future.
Co-authors
The 25 scholars most cited alongside John Quan, 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 | Overcoming catastrophic forgetting in neural networks Hit paper breakdown → | 2017 | 4665 |
| 2 | Deep Q-learning From Demonstrations Hit paper breakdown → | 2018 | 583 |
| 3 | Recurrent Experience Replay in Distributed Reinforcement Learning. | 2018 | 108 |
| 4 | Distributed Prioritized Experience Replay | 2018 | 60 |
| 5 | 2021 | 8 | |
| 6 | 2011 | 2 | |
| 7 | 2021 | 2 | |
| 8 | 2011 | 0 |
About John Quan
John Quan is a scholar working on Artificial Intelligence, Computer Science Applications, Economics and Econometrics, Signal Processing and Statistical and Nonlinear Physics, having authored 8 papers that have together received 5.4k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (4 papers), Sports Analytics and Performance (2 papers), Security and Verification in Computing (1 paper), Evolutionary Algorithms and Applications (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Smart Grid Energy Management (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Artificial Intelligence (3.9k citations), Computer Vision and Pattern Recognition (2.0k citations), Health Informatics (43 citations), Signal Processing (211 citations) and Control and Systems Engineering (433 citations). John Quan has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Guillaume Desjardins, Neil C. Rabinowitz, Demis Hassabis, Tiago Ramalho, Andrei A. Rusu, Agnieszka Grabska‐Barwińska, Kieran Milan, Clopath Claudia, James Kirkpatrick and Dharshan Kumaran. Their work appears in journals such as IT Professional, Proceedings of the National Academy of Sciences, Lecture notes in computer science, Proceedings of the AAAI Conference on Artificial Intelligence and AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)).
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.