Jan Leike
Impact in
- Software top 5%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
-
- Formal Methods in Verification
- Computability, Logic, AI Algorithms
Papers in
-
- Machine Learning and Algorithms 6
- Reinforcement Learning in Robotics 5
- Logic, Reasoning, and Knowledge 3
- Evolutionary Algorithms and Applications 3
- Logic, programming, and type systems 3
-
- Formal Methods in Verification 5
- Computability, Logic, AI Algorithms 4
- Co-authors
- Matthias Heizmann (6 shared papers)Andreas Podelski (4 shared papers)Marcus Hütter (9 shared papers)Jochen Hoenicke (1 shared paper)Daniel Dietsch (3 shared papers)Edward Hughes (3 shared papers)Dzmitry Bahdanau (3 shared papers)Tor Lattimore (2 shared papers)
- Journals
- Lecture notes in computer science (9 papers)Theoretical Computer Science (1 paper)Logical Methods in Computer Science (1 paper)International Conference on Learning Representations (1 paper)arXiv (Cornell University) (3 papers)
- Partner nations
- AustraliaGermanyUnited States
In The Last Decade
Jan Leike
18 papers receiving 201 citations
Peers
Comparison fields: 5 of 36
- Software 93
- Computational Theory and Mathematics 142
- Artificial Intelligence 146
- General Decision Sciences 4
- Hardware and Architecture 13
Countries citing papers authored by Jan Leike
This map shows the geographic impact of Jan Leike'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 Jan Leike with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Leike more than expected).
Fields of papers citing papers by Jan Leike
This network shows the impact of papers produced by Jan Leike. 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 Jan Leike. The network helps show where Jan Leike may publish in the future.
Co-authors
The 15 scholars most cited alongside Jan Leike, 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 | 2013 | 43 | |
| 2 | 2014 | 31 | |
| 3 | 2015 | 22 | |
| 4 | 2015 | 18 | |
| 5 | 2018 | 18 | |
| 6 | 2017 | 17 | |
| 7 | 2016 | 14 | |
| 8 | 2015 | 8 | |
| 9 | Bad Universal Priors and Notions of Optimality | 2015 | 6 |
| 10 | 2015 | 6 | |
| 11 | Learning to Follow Language Instructions with Adversarial Reward Induction | 2018 | 4 |
| 12 | 2017 | 4 | |
| 13 | 2014 | 4 | |
| 14 | 2015 | 4 | |
| 15 | 2014 | 3 | |
| 16 | Jointly Learning "What" and "How" from Instructions and Goal-States. | 2018 | 2 |
| 17 | 2015 | 2 | |
| 18 | 2015 | 2 | |
| 19 | 2017 | 0 | |
| 20 | Thompson sampling is asymptotically optimal in general environments | 2016 | 0 |
About Jan Leike
Jan Leike is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Software and Statistics and Probability, having authored 20 papers that have together received 208 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (6 papers), Reinforcement Learning in Robotics (5 papers), Formal Methods in Verification (5 papers), Computability, Logic, AI Algorithms (4 papers), Logic, Reasoning, and Knowledge (3 papers), Evolutionary Algorithms and Applications (3 papers), Software Testing and Debugging Techniques (3 papers) and Logic, programming, and type systems (3 papers). The work is most often cited by research in Software (93 citations), Computational Theory and Mathematics (142 citations), Artificial Intelligence (146 citations), General Decision Sciences (4 citations) and Hardware and Architecture (13 citations). Jan Leike has collaborated with scholars based in Australia, Germany and United States. Frequent co-authors include Matthias Heizmann, Andreas Podelski, Marcus Hütter, Jochen Hoenicke, Daniel Dietsch, Edward Hughes, Dzmitry Bahdanau, Tor Lattimore, Pushmeet Kohli and Edward Grefenstette. Their work appears in journals such as Lecture notes in computer science, Theoretical Computer Science, Logical Methods in Computer Science, International Conference on Learning Representations and arXiv (Cornell University).
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.