Rajat Monga
Impact in
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- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications
- Stochastic Gradient Optimization Techniques
- Speech Recognition and Synthesis
Papers in
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- Advanced Neural Network Applications 2
- Image Processing and 3D Reconstruction 1
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- Speech Recognition and Synthesis 2
- Computational Physics and Python Applications 2
- Domain Adaptation and Few-Shot Learning 2
- Neural Networks and Applications 1
- Co-authors
- Oriol VinyalsJoe Yue-Hei NgMatthew HausknechtSudheendra VijayanarasimhanGeorge TodericiQuoc V. LeGreg S. CorradoMatthieu Devin
- Journals
- International Conference on Machine Learning (1 paper)arXiv (Cornell University) (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Rajat Monga
7 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Computer Vision and Pattern Recognition 2.2k
- Artificial Intelligence 2.3k
- Signal Processing 486
- Human-Computer Interaction 166
- Hardware and Architecture 141
Countries citing papers authored by Rajat Monga
This map shows the geographic impact of Rajat Monga'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 Rajat Monga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajat Monga more than expected).
Fields of papers citing papers by Rajat Monga
This network shows the impact of papers produced by Rajat Monga. 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 Rajat Monga. The network helps show where Rajat Monga may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rajat Monga, 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 | TensorFlow.js: Machine Learning for the Web and Beyond | 2019 | 5 |
| 2 | TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning | 2019 | 1 |
| 3 | Beyond short snippets: Deep networks for video classification Hit paper breakdown → | 2015 | 1422 |
| 4 | 2014 | 96 | |
| 5 | On rectified linear units for speech processing Hit paper breakdown → | 2013 | 315 |
| 6 | Large Scale Distributed Deep Networks Hit paper breakdown → | 2012 | 1706 |
| 7 | Building high-level features using large scale unsupervised learning Hit paper breakdown → | 2012 | 406 |
| 8 | Appendix: Building high-level features using large scale unsupervised learning | 2012 | 22 |
About Rajat Monga
Rajat Monga is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Hardware and Architecture, Signal Processing and Infectious Diseases, having authored 8 papers that have together received 4.0k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (2 papers), Computational Physics and Python Applications (2 papers), Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Neural Networks and Applications (1 paper), Speech and Audio Processing (1 paper), Music and Audio Processing (1 paper) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (2.2k citations), Artificial Intelligence (2.3k citations), Signal Processing (486 citations), Human-Computer Interaction (166 citations) and Hardware and Architecture (141 citations). Rajat Monga has collaborated with scholars based in United States and Canada. Frequent co-authors include Oriol Vinyals, Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, George Toderici, Quoc V. Le, Greg S. Corrado, Matthieu Devin, Andrew Y. Ng and Marc’Aurelio Ranzato. Their work appears in journals such as International Conference on Machine Learning, arXiv (Cornell University) and Neural Information Processing Systems.
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.