Uri Shalit
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
- Computational Mathematics top 10%
Papers in
-
- Machine Learning in Healthcare 6
- Bayesian Modeling and Causal Inference 5
- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and Algorithms 3
-
- Advanced Image and Video Retrieval Techniques 4
- Image Retrieval and Classification Techniques 3
- Co-authors
- Gal Chechik (10 shared papers)Samy Bengio (3 shared papers)Varun Sharma (3 shared papers)Malka Gorfine (3 shared papers)Eran Segal (2 shared papers)Hagai Rossman (2 shared papers)Tomer Meir (2 shared papers)Smadar Shilo (2 shared papers)
- Journals
- Nature Communications (2 papers)Journal of Machine Learning Research (2 papers)Nature Medicine (1 paper)Clinical Microbiology and Infection (1 paper)Behavioural Brain Research (1 paper)
- Partner nations
- IsraelUnited StatesUnited Kingdom
In The Last Decade
Uri Shalit
30 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 142
- Modeling and Simulation 146
- Computational Mathematics 10
- Computer Vision and Pattern Recognition 314
- Statistics and Probability 113
- Health 116
Countries citing papers authored by Uri Shalit
This map shows the geographic impact of Uri Shalit'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 Uri Shalit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uri Shalit more than expected).
Fields of papers citing papers by Uri Shalit
This network shows the impact of papers produced by Uri Shalit. 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 Uri Shalit. The network helps show where Uri Shalit may publish in the future.
Co-authors
The 25 scholars most cited alongside Uri Shalit, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 299 | |
| 2 | 2021 | 145 | |
| 3 | 2019 | 129 | |
| 4 | 2020 | 77 | |
| 5 | An Online Algorithm for Large Scale Image Similarity Learning | 2009 | 69 |
| 6 | 2021 | 59 | |
| 7 | 2021 | 48 | |
| 8 | 2011 | 44 | |
| 9 | Online learning in the embedded manifold of low-rank matrices | 2012 | 26 |
| 10 | Online Learning in The Manifold of Low-Rank Matrices | 2010 | 25 |
| 11 | 2021 | 24 | |
| 12 | Modeling Musical Influence with Topic Models | 2013 | 14 |
| 13 | 2019 | 14 | |
| 14 | 2008 | 13 | |
| 15 | 2020 | 13 | |
| 16 | 2019 | 11 | |
| 17 | Coordinate-descent for learning orthogonal matrices through Givens rotations | 2014 | 9 |
| 18 | 2013 | 8 | |
| 19 | 2024 | 8 | |
| 20 | Learning Sparse Metrics, One Feature at a Time | 2015 | 7 |
About Uri Shalit
Uri Shalit is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability, Infectious Diseases and Radiology, Nuclear Medicine and Imaging, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Learning in Healthcare (6 papers), Advanced Causal Inference Techniques (5 papers), Bayesian Modeling and Causal Inference (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), COVID-19 diagnosis using AI (3 papers), Image Retrieval and Classification Techniques (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Modeling and Simulation (146 citations), Computational Mathematics (10 citations), Computer Vision and Pattern Recognition (314 citations), Statistics and Probability (113 citations) and Health (116 citations). Uri Shalit has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Gal Chechik, Samy Bengio, Varun Sharma, Malka Gorfine, Eran Segal, Hagai Rossman, Tomer Meir, Smadar Shilo, Vincent Dorie and Jennifer Hill. Their work appears in journals such as Nature Communications, Journal of Machine Learning Research, Nature Medicine, Clinical Microbiology and Infection and Behavioural Brain Research.
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.