Matt Gardner
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- Explainable Artificial Intelligence (XAI)
- Semantic Web and Ontologies
-
- Multimodal Machine Learning Applications
Papers in
-
- Topic Modeling 47
- Natural Language Processing Techniques 43
- Advanced Graph Neural Networks 4
- Domain Adaptation and Few-Shot Learning 4
- Text Readability and Simplification 4
- Adversarial Robustness in Machine Learning 3
- Speech and dialogue systems 3
-
- Multimodal Machine Learning Applications 20
- Co-authors
- Sameer Singh (22 shared papers)Pradeep Dasigi (9 shared papers)Tom M. Mitchell (6 shared papers)Jayant Krishnamurthy (4 shared papers)Partha Talukdar (5 shared papers)Dheeru Dua (7 shared papers)Gabriel Stanovsky (2 shared papers)Jonathan Berant (5 shared papers)
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)Theory and applications of categories (2 papers)npj Digital Medicine (1 paper)Journal of Business and Economic Statistics (1 paper)Science (1 paper)
- Partner nations
- United StatesIsraelIndia
In The Last Decade
Matt Gardner
62 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 1.6k
- Computer Vision and Pattern Recognition 508
- Management Science and Operations Research 120
- Health Informatics 12
- Information Systems 196
Countries citing papers authored by Matt Gardner
This map shows the geographic impact of Matt Gardner'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 Matt Gardner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matt Gardner more than expected).
Fields of papers citing papers by Matt Gardner
This network shows the impact of papers produced by Matt Gardner. 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 Matt Gardner. The network helps show where Matt Gardner may publish in the future.
Co-authors
The 25 scholars most cited alongside Matt Gardner, 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 62 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 178 | |
| 2 | 2017 | 130 | |
| 3 | 2015 | 111 | |
| 4 | 2019 | 110 | |
| 5 | 2014 | 110 | |
| 6 | 2022 | 82 | |
| 7 | 2019 | 70 | |
| 8 | 2020 | 64 | |
| 9 | 2019 | 64 | |
| 10 | 2013 | 63 | |
| 11 | 2021 | 58 | |
| 12 | 2019 | 50 | |
| 13 | 2021 | 49 | |
| 14 | 2016 | 48 | |
| 15 | 2019 | 47 | |
| 16 | 2020 | 44 | |
| 17 | 2019 | 40 | |
| 18 | 2022 | 39 | |
| 19 | 2022 | 34 | |
| 20 | 2019 | 32 |
About Matt Gardner
Matt Gardner is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability, Computer Networks and Communications and Information Systems, having authored 62 papers that have together received 1.8k indexed citations. Recurring topics across this work include Topic Modeling (47 papers), Natural Language Processing Techniques (43 papers), Multimodal Machine Learning Applications (20 papers), Advanced Graph Neural Networks (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Text Readability and Simplification (4 papers), Adversarial Robustness in Machine Learning (3 papers) and Speech and dialogue systems (3 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Computer Vision and Pattern Recognition (508 citations), Management Science and Operations Research (120 citations), Health Informatics (12 citations) and Information Systems (196 citations). Matt Gardner has collaborated with scholars based in United States, Israel and India. Frequent co-authors include Sameer Singh, Pradeep Dasigi, Tom M. Mitchell, Jayant Krishnamurthy, Partha Talukdar, Dheeru Dua, Gabriel Stanovsky, Jonathan Berant, Sanjay Subramanian and Yizhong Wang. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Theory and applications of categories, npj Digital Medicine, Journal of Business and Economic Statistics and Science.
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.