Joel Lehman
About
In The Last Decade
Joel Lehman
50 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Artificial Intelligence 1.6k
- Computational Theory and Mathematics 295
- Sociology and Political Science 246
- Computer Vision and Pattern Recognition 238
- Mechanical Engineering 234
Countries citing papers authored by Joel Lehman
This map shows the geographic impact of Joel Lehman'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 Joel Lehman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joel Lehman more than expected).
Fields of papers citing papers by Joel Lehman
This network shows the impact of papers produced by Joel Lehman. 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 Joel Lehman. The network helps show where Joel Lehman may publish in the future.
Co-authorship network of co-authors of Joel Lehman
This figure shows the co-authorship network connecting the top 25 collaborators of Joel Lehman. A scholar is included among the top collaborators of Joel Lehman 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 Joel Lehman. Joel Lehman 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 | 18 | |
| 3 | Reinforcement Learning Under Moral Uncertainty | 1 |
| 4 | Learning Belief Representations for Imitation Learning in POMDPs | 2 |
| 5 | Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents | 51 |
| 6 | Creative Generation of 3D Objects with Deep Learning and Innovation Engines. | 19 |
| 7 | 19 | |
| 8 | 23 | |
| 9 | 50 | |
| 10 | 9 | |
| 11 | 15 | |
| 12 | 15 | |
| 13 | 40 | |
| 14 | 34 | |
| 15 | 12 | |
| 16 | EVOLUTION THROUGH THE SEARCH FOR NOVELTY | 8 |
| 17 | Improving Evolvability through Novelty Search and Self-Adaptation In: Proceedings of the 2011 IEEE Congress on Evolutionary Computation (CEC 2011). Piscataway, NJ: IEEE | 2 |
| 18 | 33 | |
| 19 | 124 | |
| 20 | Exploiting Open-Endedness to Solve Problems Through the Search for Novelty | 214 |
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.