Jason Eisner
- Artificial Intelligence top 0.2%
- Natural Language Processing Techniques 106
- Topic Modeling 92
- Machine Learning and Algorithms 21
- Algorithms and Data Compression 21
- Speech and dialogue systems 20
- Speech Recognition and Synthesis 13
- Text Readability and Simplification 10
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- semigroups and automata theory 12
- Information Systems top 2%
- Signal Processing top 5%
- Co-authors
- Noah A. SmithDavid A. SmithGuanghui QinMarkus DreyerRyan CotterellOmar F. ZaidanGiorgio SattaZhifei Li
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Journals
- Transactions of the Association for Computational Linguistics (8 papers)Cognitive Science (4 papers)Computational Linguistics (1 paper)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Jason Eisner
137 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 3.6k
- Computer Vision and Pattern Recognition 514
- Computational Theory and Mathematics 214
- Information Systems 262
- Signal Processing 120
Countries citing papers authored by Jason Eisner
This map shows the geographic impact of Jason Eisner'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 Jason Eisner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Eisner more than expected).
Fields of papers citing papers by Jason Eisner
This network shows the impact of papers produced by Jason Eisner. 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 Jason Eisner. The network helps show where Jason Eisner may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jason Eisner, 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 | 2024 | 12 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 1 | |
| 5 | Noise-Contrastive Estimation for Multivariate Point Processes | 2020 | 2 |
| 6 | UniMorph 2.0: Universal Morphology | 2018 | 7 |
| 7 | 2016 | 30 | |
| 8 | Imitation Learning by Coaching | 2012 | 46 |
| 9 | Minimum-Risk Training of Approximate CRF-Based NLP Systems | 2012 | 13 |
| 10 | Implicitly Intersecting Weighted Automata using Dual Decomposition | 2012 | 7 |
| 11 | Shared Components Topic Models | 2012 | 9 |
| 12 | Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure | 2011 | 44 |
| 13 | Compiling Comp Ling: Weighted Dynamic Programming and the Dyna Language | 2005 | 27 |
| 14 | 2002 | 7 | |
| 15 | 2002 | 6 | |
| 16 | Proceedings of the Fifth Workshop of the ACL Special Interest Group in Computational Phonology | 2000 | 1 |
| 17 | Easy and Hard Constraint Ranking in OT: Algorithms and Complexity | 2000 | 0 |
| 18 | 1997 | 11 | |
| 19 | 1997 | 60 | |
| 20 | Bilexical Grammars and a Cubic-time Probabilistic Parser | 1997 | 42 |
About Jason Eisner
Jason Eisner is a scholar working on Artificial Intelligence, Computational Mathematics and Computational Theory and Mathematics, having authored 147 papers that have together received 4.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (106 papers), Topic Modeling (92 papers), Machine Learning and Algorithms (21 papers), Algorithms and Data Compression (21 papers), Speech and dialogue systems (20 papers), Speech Recognition and Synthesis (13 papers), semigroups and automata theory (12 papers) and Text Readability and Simplification (10 papers). The work is most often cited by research in Artificial Intelligence (3.6k citations), Computer Vision and Pattern Recognition (514 citations) and Computational Theory and Mathematics (214 citations). Jason Eisner has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Noah A. Smith, David A. Smith, Guanghui Qin, Markus Dreyer, Ryan Cotterell, Omar F. Zaidan, Giorgio Satta, Zhifei Li, He He and Christine Piatko. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Cognitive Science, Computational Linguistics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Radiographics.
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.