Chitwan Saharia
- Computer Vision and Pattern Recognition top 1%
- Media Technology top 2%
- Artificial Intelligence top 10%
- Computer Graphics and Computer-Aided Design top 2%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Mohammad NorouziDavid J. FleetJonathan HoTim SalimansWilliam ChanYoshua BengioMaxime Chevalier-BoisvertDzmitry Bahdanau
- Topics
- Generative Adversarial Networks and Image Synthesis (3 papers)Natural Language Processing Techniques (3 papers)Topic Modeling (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignMedia Technology
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencearXiv (Cornell University)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Chitwan Saharia
7 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Computer Vision and Pattern Recognition 838
- Media Technology 247
- Artificial Intelligence 169
- Computer Graphics and Computer-Aided Design 103
- Radiology, Nuclear Medicine and Imaging 102
Countries citing papers authored by Chitwan Saharia
This map shows the geographic impact of Chitwan Saharia'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 Chitwan Saharia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chitwan Saharia more than expected).
Fields of papers citing papers by Chitwan Saharia
This network shows the impact of papers produced by Chitwan Saharia. 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 Chitwan Saharia. The network helps show where Chitwan Saharia may publish in the future.
Co-authorship network of co-authors of Chitwan Saharia
This figure shows the co-authorship network connecting the top 25 collaborators of Chitwan Saharia. A scholar is included among the top collaborators of Chitwan Saharia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chitwan Saharia. Chitwan Saharia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 66 | |
| 3 | 47 | |
| 4 | Image Super-Resolution Via Iterative Refinementbreakdown → | 1022 |
| 5 | 2 | |
| 6 | BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop. | 25 |
| 7 | 22 |
About Chitwan Saharia
Chitwan Saharia is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 7 papers that have together received 1.2k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Natural Language Processing Techniques (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (838 citations), Computer Graphics and Computer-Aided Design (103 citations) and Media Technology (247 citations). Chitwan Saharia has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Mohammad Norouzi, David J. Fleet, Jonathan Ho, Tim Salimans, William Chan, William Chan, Yoshua Bengio, Maxime Chevalier-Boisvert, Dzmitry Bahdanau and Thien Huu Nguyen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence 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.