Myle Ott
- Artificial Intelligence top 0.2%
- Topic Modeling 14
- Natural Language Processing Techniques 11
- Hate Speech and Cyberbullying Detection 4
- Information Systems top 0.5%
- Spam and Phishing Detection 7
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- Multimodal Machine Learning Applications 6
- Signal Processing top 2%
- Health Informatics top 5%
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- Misinformation and Its Impacts 6
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- Deception detection and forensic psychology 3
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- Computational and Text Analysis Methods 2
- Co-authors
- Claire CardieMichael AuliSergey EdunovDavid GrangierJeffrey T. HancockNathan NgAlexei BaevskiSam Gross
- Journals
- Journal of the Association for Information Systems (1 paper)Proceedings of the National Academy of Sciences (1 paper)Proceedings of the VLDB Endowment (1 paper)
- Partner nations
- United StatesIsraelHong Kong
In The Last Decade
Myle Ott
24 papers receiving 5.0k citations
Hit Papers
Peers
Comparison fields: 5 of 162
- Artificial Intelligence 3.3k
- Information Systems 1.0k
- Computer Vision and Pattern Recognition 830
- Signal Processing 361
- Health Informatics 28
Countries citing papers authored by Myle Ott
This map shows the geographic impact of Myle Ott'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 Myle Ott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Myle Ott more than expected).
Fields of papers citing papers by Myle Ott
This network shows the impact of papers produced by Myle Ott. 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 Myle Ott. The network helps show where Myle Ott may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Myle Ott, 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 | PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallelbreakdown → | 2023 | 83 |
| 2 | Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequencesbreakdown → | 2021 | 1429 |
| 3 | 2021 | 22 | |
| 4 | 2020 | 93 | |
| 5 | Energy-Based Models for Text | 2020 | 2 |
| 6 | 2020 | 3 | |
| 7 | 2019 | 165 | |
| 8 | Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models | 2019 | 4 |
| 9 | fairseq: A Fast, Extensible Toolkit for Sequence Modelingbreakdown → | 2019 | 1381 |
| 10 | 2019 | 24 | |
| 11 | Understanding Back-Translation at Scalebreakdown → | 2018 | 539 |
| 12 | 2018 | 252 | |
| 13 | Impact of Mobility and Timing on User-Generated Content | 2014 | 26 |
| 14 | 2014 | 237 | |
| 15 | 2014 | 1 | |
| 16 | Negative Deceptive Opinion Spam | 2013 | 191 |
| 17 | 2013 | 26 | |
| 18 | In Search of a Gold Standard in Studies of Deception | 2012 | 25 |
| 19 | 2012 | 186 | |
| 20 | 2011 | 159 |
About Myle Ott
Myle Ott is a scholar working on General Social Sciences, Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition and Sociology and Political Science, having authored 24 papers that have together received 5.3k indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (11 papers), Spam and Phishing Detection (7 papers), Misinformation and Its Impacts (6 papers), Multimodal Machine Learning Applications (6 papers), Hate Speech and Cyberbullying Detection (4 papers), Deception detection and forensic psychology (3 papers) and Computational and Text Analysis Methods (2 papers). The work is most often cited by research in Artificial Intelligence (3.3k citations), Information Systems (1.0k citations), Computer Vision and Pattern Recognition (830 citations), Signal Processing (361 citations) and Health Informatics (28 citations). Myle Ott has collaborated with scholars based in United States, Israel and Hong Kong. Frequent co-authors include Claire Cardie, Michael Auli, Sergey Edunov, David Grangier, Jeffrey T. Hancock, Nathan Ng, Alexei Baevski, Sam Gross, Angela Fan and Alexander Rives. Their work appears in journals such as Journal of the Association for Information Systems, Proceedings of the National Academy of Sciences, Proceedings of the VLDB Endowment, North American Chapter of the Association for Computational Linguistics and arXiv (Cornell University).
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.