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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- Computational Physics and Python Applications 2
- Speech Recognition and Synthesis 2
- Domain Adaptation and Few-Shot Learning 2
- Neural Networks and Applications 1
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- Advanced Neural Network Applications 2
- Advanced Vision and Imaging 1
- Human Pose and Action Recognition 1
- Co-authors
- Oriol Vinyals (2 shared papers)George Toderici (1 shared paper)Matthew Hausknecht (1 shared paper)Sudheendra Vijayanarasimhan (1 shared paper)Joe Yue-Hei Ng (1 shared paper)Quoc V. Le (4 shared papers)Andrew Y. Ng (3 shared papers)Greg S. Corrado (4 shared papers)
- Journals
- arXiv (Cornell University) (1 paper)Neural Information Processing Systems (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Rajat Monga
7 papers receiving 3.8k citations
Rajat Monga's Hit Papers
Peers
Comparison fields: 5 of 152
- Computer Vision and Pattern Recognition 2.3k
- Artificial Intelligence 2.3k
- Signal Processing 483
- Human-Computer Interaction 171
- 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-authors
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 | Large Scale Distributed Deep Networks Hit paper breakdown → | 2012 | 1718 |
| 2 | Beyond short snippets: Deep networks for video classification Hit paper breakdown → | 2015 | 1443 |
| 3 | Building high-level features using large scale unsupervised learning Hit paper breakdown → | 2012 | 406 |
| 4 | On rectified linear units for speech processing Hit paper breakdown → | 2013 | 316 |
| 5 | 2014 | 95 | |
| 6 | Appendix: Building high-level features using large scale unsupervised learning | 2012 | 22 |
| 7 | TensorFlow.js: Machine Learning for the Web and Beyond | 2019 | 5 |
| 8 | TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning | 2019 | 1 |
About Rajat Monga
Rajat Monga is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Hardware and Architecture and Infectious Diseases, having authored 8 papers that have together received 4.0k indexed citations. Recurring topics across this work include Computational Physics and Python Applications (2 papers), Speech Recognition and Synthesis (2 papers), Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Advanced Vision and Imaging (1 paper), Music and Audio Processing (1 paper), Neural Networks and Applications (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (2.3k citations), Artificial Intelligence (2.3k citations), Signal Processing (483 citations), Human-Computer Interaction (171 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, George Toderici, Matthew Hausknecht, Sudheendra Vijayanarasimhan, Joe Yue-Hei Ng, Quoc V. Le, Andrew Y. Ng, Greg S. Corrado, Matthieu Devin and Marc’Aurelio Ranzato. Their work appears in journals such as arXiv (Cornell University), Neural Information Processing Systems and International Conference on Machine Learning.
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.