Jacob Buckman
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Signal Processing
- Electrical and Electronic Engineering
- Molecular Biology
- Co-authors
- Aurko RoyIan GoodfellowColin RaffelDanijar HafnerMiguel BallesterosChris DyerEugene BrevdoHonglak Lee
- Topics
- Multimodal Machine Learning Applications (1 paper)Advanced Multi-Objective Optimization Algorithms (1 paper)Adversarial Robustness in Machine Learning (1 paper)
- Journals
- Neural Information Processing SystemsInternational Conference on Learning Representations
- Partner nations
- United States
In The Last Decade
Jacob Buckman
3 papers receiving 192 citations
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 184
- Computer Vision and Pattern Recognition 52
- Signal Processing 42
- Electrical and Electronic Engineering 40
- Molecular Biology 35
Countries citing papers authored by Jacob Buckman
This map shows the geographic impact of Jacob Buckman'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 Jacob Buckman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob Buckman more than expected).
Fields of papers citing papers by Jacob Buckman
This network shows the impact of papers produced by Jacob Buckman. 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 Jacob Buckman. The network helps show where Jacob Buckman may publish in the future.
Co-authorship network of co-authors of Jacob Buckman
This figure shows the co-authorship network connecting the top 25 collaborators of Jacob Buckman. A scholar is included among the top collaborators of Jacob Buckman 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 Jacob Buckman. Jacob Buckman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion | 10 |
| 2 | Thermometer Encoding: One Hot Way To Resist Adversarial Examples | 193 |
| 3 | 5 |
About Jacob Buckman
Jacob Buckman is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 3 papers that have together received 208 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (1 paper), Advanced Multi-Objective Optimization Algorithms (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Artificial Intelligence (184 citations), Signal Processing (42 citations) and Computer Vision and Pattern Recognition (52 citations). Jacob Buckman has collaborated with scholars based in United States. Frequent co-authors include Aurko Roy, Ian Goodfellow, Colin Raffel, Danijar Hafner, Miguel Ballesteros, Chris Dyer, Eugene Brevdo, Honglak Lee and George Tucker. Their work appears in journals such as Neural Information Processing Systems and International Conference on Learning Representations.
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.