Christoph Dann
- Artificial Intelligence top 10%
- Computer Science Applications top 5%
- Management Science and Operations Research top 10%
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics top 10%
- Co-authors
- Eric P. XingAndrew Gordon WilsonChristopher G. LucasGerhard NeumannJan PetersEmma BrunskillRené F. KizilcecJustin Reich
- Topics
- Reinforcement Learning in Robotics (7 papers)Advanced Bandit Algorithms Research (3 papers)Evolutionary Algorithms and Applications (2 papers)
- Journals
- Proceedings of the National Academy of SciencesIEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Machine Learning Research
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Christoph Dann
13 papers receiving 387 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 189
- Computer Science Applications 57
- Management Science and Operations Research 54
- Computer Vision and Pattern Recognition 47
- Computational Theory and Mathematics 46
Countries citing papers authored by Christoph Dann
This map shows the geographic impact of Christoph Dann'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 Christoph Dann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christoph Dann more than expected).
Fields of papers citing papers by Christoph Dann
This network shows the impact of papers produced by Christoph Dann. 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 Christoph Dann. The network helps show where Christoph Dann may publish in the future.
Co-authorship network of co-authors of Christoph Dann
This figure shows the co-authorship network connecting the top 25 collaborators of Christoph Dann. A scholar is included among the top collaborators of Christoph Dann 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 Christoph Dann. Christoph Dann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations | 1 |
| 3 | Dynamic Balancing for Model Selection in Bandits and RL | 1 |
| 4 | 100 | |
| 5 | 1 | |
| 6 | Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning | 20 |
| 7 | 29 | |
| 8 | Energetic natural gradient descent | 2 |
| 9 | 27 | |
| 10 | Sample complexity of episodic fixed-horizon reinforcement learning | 9 |
| 11 | The human kernel | 6 |
| 12 | RLPy: a value-function-based reinforcement learning framework for education and research | 17 |
| 13 | Proceedings for 20th Annual Conference on Neural Information Processing Systems (NIPS) | 117 |
| 14 | Policy evaluation with temporal differences: a survey and comparison | 75 |
About Christoph Dann
Christoph Dann is a scholar working on Computational Mathematics, Management Science and Operations Research and Instrumentation, having authored 14 papers that have together received 406 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Advanced Bandit Algorithms Research (3 papers) and Evolutionary Algorithms and Applications (2 papers). The work is most often cited by research in Computer Science Applications (57 citations), Artificial Intelligence (189 citations) and Instrumentation (20 citations). Christoph Dann has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Eric P. Xing, Andrew Gordon Wilson, Christopher G. Lucas, Gerhard Neumann, Jan Peters, Emma Brunskill, René F. Kizilcec, Justin Reich, Michael Yeomans and Dustin Tingley. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Machine Learning Research.
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.