Chen Tessler
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
- Domain Adaptation and Few-Shot Learning
- Data Stream Mining Techniques
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- Multimodal Machine Learning Applications
Papers in ⓘ
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- Reinforcement Learning in Robotics 4
- Adversarial Robustness in Machine Learning 2
- Artificial Intelligence in Games 1
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- Human Motion and Animation 2
- Co-authors
- Shie Mannor (6 shared papers)Daniel J. Mankowitz (2 shared papers)Tom Zahavy (1 shared paper)Gal Chechik (4 shared papers)Gal Dalal (2 shared papers)Benjamin Fuhrer (2 shared papers)Yunrong Guo (1 shared paper)Yifeng Jiang (1 shared paper)
- Journals
- ACM Transactions on Graphics (1 paper)Computer Graphics Forum (1 paper)ACM SIGMETRICS Performance Evaluation Review (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
- Partner nations
- IsraelUnited StatesUnited Kingdom
In The Last Decade
Chen Tessler
9 papers receiving 158 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 104
- Computer Vision and Pattern Recognition 39
- Control and Systems Engineering 33
- Computer Networks and Communications 30
- Computer Science Applications 6
Countries citing papers authored by Chen Tessler
This map shows the geographic impact of Chen Tessler'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 Chen Tessler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chen Tessler more than expected).
Fields of papers citing papers by Chen Tessler
This network shows the impact of papers produced by Chen Tessler. 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 Chen Tessler. The network helps show where Chen Tessler may publish in the future.
Co-authors
The 15 scholars most cited alongside Chen Tessler, 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 | 2017 | 116 | |
| 2 | 2022 | 17 | |
| 3 | Reward Constrained Policy Optimization | 2018 | 11 |
| 4 | Action Robust Reinforcement Learning and Applications in Continuous Control | 2019 | 9 |
| 5 | 2024 | 7 | |
| 6 | 2022 | 2 | |
| 7 | 2024 | 1 | |
| 8 | Stabilizing Off-Policy Reinforcement Learning with Conservative Policy Gradients | 2019 | 1 |
| 9 | 2022 | 1 | |
| 10 | 2025 | 0 |
About Chen Tessler
Chen Tessler is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications and Information Systems, having authored 10 papers that have together received 165 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (4 papers), Cloud Computing and Resource Management (2 papers), Human Pose and Action Recognition (2 papers), Software-Defined Networks and 5G (2 papers), Human Motion and Animation (2 papers), Adversarial Robustness in Machine Learning (2 papers), Artificial Intelligence in Games (1 paper) and Adaptive Dynamic Programming Control (1 paper). The work is most often cited by research in Artificial Intelligence (104 citations), Computer Vision and Pattern Recognition (39 citations), Control and Systems Engineering (33 citations), Computer Networks and Communications (30 citations) and Computer Science Applications (6 citations). Chen Tessler has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Shie Mannor, Daniel J. Mankowitz, Tom Zahavy, Gal Chechik, Gal Dalal, Benjamin Fuhrer, Yunrong Guo, Yifeng Jiang, Iuri Frosio and Gilbert Bernstein. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum, ACM SIGMETRICS Performance Evaluation Review, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.