Rafael Rafailov

44 total papers · 810 total citations
3 papers, 52 citations indexed

About

Rafael Rafailov is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Rafael Rafailov has authored 3 papers receiving a total of 52 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Computational Theory and Mathematics. Recurrent topics in Rafael Rafailov's work include Generative Adversarial Networks and Image Synthesis (1 paper), Natural Language Processing Techniques (1 paper) and Reinforcement Learning in Robotics (1 paper). Rafael Rafailov is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (1 paper), Natural Language Processing Techniques (1 paper) and Reinforcement Learning in Robotics (1 paper). Rafael Rafailov collaborates with scholars based in United States. Rafael Rafailov's co-authors include Chelsea Finn, Eric Mitchell, Christopher D. Manning, Archit Sharma, Huaxiu Yao, Aaron Lou, Nikhil Naik, Stefano Ermon, Senthil Purushwalkam and Caiming Xiong and has published in prestigious journals such as .

In The Last Decade

Rafael Rafailov

3 papers receiving 50 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Rafael Rafailov 34 10 5 5 4 3 52
Ayesha Bajwa 48 1.4× 7 0.7× 5 1.0× 7 1.4× 6 1.5× 4 65
Mohammad Al Sa’d 28 0.8× 26 2.6× 5 1.0× 5 1.0× 2 0.5× 3 58
Huazuo Gao 18 0.5× 7 0.7× 6 1.2× 3 0.6× 2 0.5× 3 53
Pierre Stock 35 1.0× 15 1.5× 2 0.4× 5 1.0× 3 0.8× 4 53
Xiang Lisa Li 53 1.6× 14 1.4× 6 1.2× 2 0.4× 2 0.5× 4 67
Peitian Zhang 37 1.1× 8 0.8× 17 3.4× 4 0.8× 7 1.8× 4 70
Nanziba Basnin 20 0.6× 4 0.4× 5 1.0× 5 1.0× 2 0.5× 3 67
Wangding Zeng 21 0.6× 21 2.1× 6 1.2× 3 0.6× 2 0.5× 3 66
Prajjwal Bhargava 55 1.6× 14 1.4× 10 2.0× 2 0.4× 4 1.0× 3 67
Rohan Taori 29 0.9× 16 1.6× 6 1.2× 5 1.0× 1 0.3× 5 44

Countries citing papers authored by Rafael Rafailov

Since Specialization
Citations

This map shows the geographic impact of Rafael Rafailov'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 Rafael Rafailov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafael Rafailov more than expected).

Fields of papers citing papers by Rafael Rafailov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rafael Rafailov. 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 Rafael Rafailov. The network helps show where Rafael Rafailov may publish in the future.

Co-authorship network of co-authors of Rafael Rafailov

This figure shows the co-authorship network connecting the top 25 collaborators of Rafael Rafailov. A scholar is included among the top collaborators of Rafael Rafailov 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 Rafael Rafailov. Rafael Rafailov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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