Timothy Mann
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Machine Learning and Algorithms
- AI-based Problem Solving and Planning
- Evolutionary Algorithms and Applications
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- Advanced Bandit Algorithms Research
Papers in
-
- Reinforcement Learning in Robotics 15
- Machine Learning and Algorithms 8
- Adversarial Robustness in Machine Learning 7
- Evolutionary Algorithms and Applications 3
- AI-based Problem Solving and Planning 3
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- Advanced Bandit Algorithms Research 4
- Co-authors
- Shie Mannor (11 shared papers)Yoonsuck Choe (8 shared papers)Sven Gowal (7 shared papers)Pushmeet Kohli (3 shared papers)Krishnamurthy Dvijotham (3 shared papers)Robert Stanforth (2 shared papers)Daniel J. Mankowitz (7 shared papers)Jonathan Uesato (1 shared paper)
- Journals
- BMC Neuroscience (1 paper)Behavioral and Brain Sciences (1 paper)Journal of Artificial Intelligence Research (1 paper)Journal of Pharmacy Practice and Research (1 paper)ICGA Journal (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Timothy Mann
32 papers receiving 234 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 200
- Management Science and Operations Research 41
- Computer Vision and Pattern Recognition 38
- Hardware and Architecture 12
- Computational Theory and Mathematics 27
Countries citing papers authored by Timothy Mann
This map shows the geographic impact of Timothy Mann'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 Timothy Mann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timothy Mann more than expected).
Fields of papers citing papers by Timothy Mann
This network shows the impact of papers produced by Timothy Mann. 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 Timothy Mann. The network helps show where Timothy Mann may publish in the future.
Co-authors
The 25 scholars most cited alongside Timothy Mann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 79 | |
| 2 | Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations | 2014 | 21 |
| 3 | 2015 | 16 | |
| 4 | Directed Exploration in Reinforcement Learning with Transferred Knowledge | 2012 | 14 |
| 5 | How hard is my MDP?" The distribution-norm to the rescue" | 2014 | 11 |
| 6 | Adaptive Skills Adaptive Partitions (ASAP) | 2016 | 9 |
| 7 | 2018 | 8 | |
| 8 | Time-regularized interrupting options | 2014 | 8 |
| 9 | 2018 | 7 | |
| 10 | Off-policy Model-based Learning under Unknown Factored Dynamics | 2015 | 6 |
| 11 | 2012 | 6 | |
| 12 | Self-supervised Adversarial Robustness for the Low-label, High-data Regime | 2021 | 6 |
| 13 | 2011 | 5 | |
| 14 | Time-Regularized Interrupting Options (TRIO) | 2014 | 5 |
| 15 | 2021 | 5 | |
| 16 | A Bayesian Approach to Robust Reinforcement Learning | 2019 | 4 |
| 17 | 2019 | 4 | |
| 18 | 2010 | 4 | |
| 19 | Learning from Delayed Outcomes with Intermediate Observations | 2018 | 3 |
| 20 | Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates | 2019 | 3 |
About Timothy Mann
Timothy Mann is a scholar working on Artificial Intelligence, Management Science and Operations Research, Cognitive Neuroscience, Computer Networks and Communications and Information Systems, having authored 35 papers that have together received 246 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (15 papers), Machine Learning and Algorithms (8 papers), Adversarial Robustness in Machine Learning (7 papers), Advanced Bandit Algorithms Research (4 papers), Evolutionary Algorithms and Applications (3 papers), Action Observation and Synchronization (3 papers), AI-based Problem Solving and Planning (3 papers) and Recommender Systems and Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (200 citations), Management Science and Operations Research (41 citations), Computer Vision and Pattern Recognition (38 citations), Hardware and Architecture (12 citations) and Computational Theory and Mathematics (27 citations). Timothy Mann has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Shie Mannor, Yoonsuck Choe, Sven Gowal, Pushmeet Kohli, Krishnamurthy Dvijotham, Robert Stanforth, Daniel J. Mankowitz, Jonathan Uesato, Relja Arandjelović and Rudy Bunel. Their work appears in journals such as BMC Neuroscience, Behavioral and Brain Sciences, Journal of Artificial Intelligence Research, Journal of Pharmacy Practice and Research and ICGA Journal.
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.