Jeff Dean
Impact in
- Health Informatics top 0.05%
- Artificial Intelligence top 0.02%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Domain Adaptation and Few-Shot Learning
- Text and Document Classification Technologies
Papers in
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- Domain Adaptation and Few-Shot Learning 4
- Topic Modeling 2
- Machine Learning and Data Classification 2
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- Advanced Neural Network Applications 4
- Co-authors
- Greg S. Corrado (6 shared papers)Tomáš Mikolov (2 shared papers)Ilya Sutskever (1 shared paper)Kai Chen (1 shared paper)Katherine Chou (3 shared papers)Andre Esteva (2 shared papers)Sebastian Thrun (1 shared paper)Mark A. DePristo (1 shared paper)
- Journals
- Nature (2 papers)npj Digital Medicine (1 paper)Computer (1 paper)Nature Medicine (1 paper)IEEE Micro (1 paper)
- Partner nations
- United StatesIsraelPoland
In The Last Decade
Jeff Dean
21 papers receiving 16.0k citations
Jeff Dean's Hit Papers
Peers
Comparison fields: 5 of 218
- Health Informatics 696
- Artificial Intelligence 11.1k
- Computer Vision and Pattern Recognition 3.7k
- Information Systems 2.2k
- Health Information Management 352
Countries citing papers authored by Jeff Dean
This map shows the geographic impact of Jeff Dean'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 Jeff Dean with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Dean more than expected).
Fields of papers citing papers by Jeff Dean
This network shows the impact of papers produced by Jeff Dean. 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 Jeff Dean. The network helps show where Jeff Dean may publish in the future.
Co-authors
The 25 scholars most cited alongside Jeff Dean, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Distributed Representations of Words and Phrases and their Compositionality Hit paper breakdown → | 2013 | 10679 |
| 2 | A guide to deep learning in healthcare Hit paper breakdown → | 2018 | 2528 |
| 3 | DeViSE: A Deep Visual-Semantic Embedding Model Hit paper breakdown → | 2013 | 1155 |
| 4 | Deep learning-enabled medical computer vision Hit paper breakdown → | 2021 | 772 |
| 5 | Efficient Neural Architecture Search via Parameters Sharing Hit paper breakdown → | 2018 | 603 |
| 6 | Building high-level features using large scale unsupervised learning Hit paper breakdown → | 2012 | 406 |
| 7 | A graph placement methodology for fast chip design Hit paper breakdown → | 2021 | 339 |
| 8 | The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink Hit paper breakdown → | 2022 | 181 |
| 9 | 2017 | 121 | |
| 10 | 2018 | 103 | |
| 11 | A Hierarchical Model for Device Placement | 2018 | 55 |
| 12 | 2020 | 27 | |
| 13 | 2022 | 27 | |
| 14 | Appendix: Building high-level features using large scale unsupervised learning | 2012 | 22 |
| 15 | Faster Discovery of Neural Architectures by Searching for Paths in a Large Model | 2018 | 7 |
| 16 | 2024 | 4 | |
| 17 | 2023 | 4 | |
| 18 | 2019 | 3 | |
| 19 | 2016 | 3 | |
| 20 | 2015 | 3 |
About Jeff Dean
Jeff Dean is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering, having authored 22 papers that have together received 17.0k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), COVID-19 diagnosis using AI (3 papers), Photography and Visual Culture (2 papers), Embedded Systems Design Techniques (2 papers), VLSI and FPGA Design Techniques (2 papers), Topic Modeling (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Health Informatics (696 citations), Artificial Intelligence (11.1k citations), Computer Vision and Pattern Recognition (3.7k citations), Information Systems (2.2k citations) and Health Information Management (352 citations). Jeff Dean has collaborated with scholars based in United States, Israel and Poland. Frequent co-authors include Greg S. Corrado, Tomáš Mikolov, Ilya Sutskever, Kai Chen, Katherine Chou, Andre Esteva, Sebastian Thrun, Mark A. DePristo, Bharath Ramsundar and Volodymyr Kuleshov. Their work appears in journals such as Nature, npj Digital Medicine, Computer, Nature Medicine and IEEE Micro.
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.