Dan Friedman
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Advanced Text Analysis Techniques
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
Papers in
-
- Theatre and Performance Studies 7
-
- Topic Modeling 6
- Natural Language Processing Techniques 5
- Domain Adaptation and Few-Shot Learning 3
- Evolutionary Algorithms and Applications 2
- Co-authors
- Danqi Chen (7 shared papers)Zexuan Zhong (1 shared paper)Jungo Kasai (3 shared papers)Dragomir Radev (2 shared papers)Rui Zhang (1 shared paper)Irene Li (1 shared paper)Alexander R. Fabbri (1 shared paper)Michihiro Yasunaga (1 shared paper)
- Journals
- TDR/The Drama Review (3 papers)Proceedings of the National Academy of Sciences (1 paper)ACM SIGCOMM Computer Communication Review (1 paper)Topoi (1 paper)Maryland law review (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Dan Friedman
25 papers receiving 463 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 364
- Health Informatics 6
- Computer Vision and Pattern Recognition 54
- Statistics, Probability and Uncertainty 14
- History and Philosophy of Science 16
Countries citing papers authored by Dan Friedman
This map shows the geographic impact of Dan Friedman'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 Dan Friedman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Friedman more than expected).
Fields of papers citing papers by Dan Friedman
This network shows the impact of papers produced by Dan Friedman. 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 Dan Friedman. The network helps show where Dan Friedman may publish in the future.
Co-authors
The 20 scholars most cited alongside Dan Friedman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 199 | |
| 2 | 2019 | 137 | |
| 3 | 2024 | 47 | |
| 4 | 2019 | 23 | |
| 5 | 1989 | 14 | |
| 6 | 2021 | 13 | |
| 7 | 2023 | 8 | |
| 8 | 2004 | 5 | |
| 9 | Linguistically Rich Vector Representations of Supertags for TAG Parsing | 2017 | 5 |
| 10 | 2022 | 5 | |
| 11 | 2023 | 4 | |
| 12 | 1993 | 2 | |
| 13 | Angels in the American Theater: Patrons, Patronage, and Philanthropy | 2007 | 2 |
| 14 | 2011 | 2 | |
| 15 | 2021 | 2 | |
| 16 | Dan Friedman: Radical Modernism | 1994 | 1 |
| 17 | 1995 | 1 | |
| 18 | Magnificent Failure Revisited: Modern Maryland Constitutional Law from 1967 to 1998 | 1999 | 1 |
| 19 | 2000 | 1 | |
| 20 | 2004 | 1 |
About Dan Friedman
Dan Friedman is a scholar working on Visual Arts and Performing Arts, Artificial Intelligence, Architecture, Computer Science Applications and Political Science and International Relations, having authored 30 papers that have together received 481 indexed citations. Recurring topics across this work include Theatre and Performance Studies (7 papers), Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers), Domain Adaptation and Few-Shot Learning (3 papers), American Constitutional Law and Politics (3 papers), Legal and Constitutional Studies (2 papers), Evolutionary Algorithms and Applications (2 papers) and Architecture, Modernity, and Design (2 papers). The work is most often cited by research in Artificial Intelligence (364 citations), Health Informatics (6 citations), Computer Vision and Pattern Recognition (54 citations), Statistics, Probability and Uncertainty (14 citations) and History and Philosophy of Science (16 citations). Dan Friedman has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Danqi Chen, Zexuan Zhong, Jungo Kasai, Dragomir Radev, Rui Zhang, Irene Li, Alexander R. Fabbri, Michihiro Yasunaga, Richard Thomas McCoy and Thomas L. Griffiths. Their work appears in journals such as TDR/The Drama Review, Proceedings of the National Academy of Sciences, ACM SIGCOMM Computer Communication Review, Topoi and Maryland law review.
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.