Ravi Krishna

519 total citations
6 papers, 329 citations indexed

About

Ravi Krishna is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology. According to data from OpenAlex, Ravi Krishna has authored 6 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 1 paper in Experimental and Cognitive Psychology. Recurrent topics in Ravi Krishna's work include Domain Adaptation and Few-Shot Learning (4 papers), Multimodal Machine Learning Applications (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Ravi Krishna is often cited by papers focused on Domain Adaptation and Few-Shot Learning (4 papers), Multimodal Machine Learning Applications (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Ravi Krishna collaborates with scholars based in United States and China. Ravi Krishna's co-authors include Kurt Keutzer, Sicheng Zhao, Xiangyu Yue, Alberto Sangiovanni‐Vincentelli, BoRui Wu, Shanghang Zhang, Sanjit A. Seshia, Han Zhao, Joseph E. Gonzalez and Bo Li and has published in prestigious journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems and ACM Transactions on Asian and Low-Resource Language Information Processing.

In The Last Decade

Ravi Krishna

6 papers receiving 323 citations

Peers

Ravi Krishna
Hongliang Yan China
Yukang Ding China
Jin Yuan China
Dapeng Hu China
Sara Sabour United States
Kalyan Vasudev Alwala United States
Waldir R. De Almeida Brazil
Wenju Xu United States
Zizhao Wu China
Hongliang Yan China
Ravi Krishna
Citations per year, relative to Ravi Krishna Ravi Krishna (= 1×) peers Hongliang Yan

Countries citing papers authored by Ravi Krishna

Since Specialization
Citations

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

Fields of papers citing papers by Ravi Krishna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ravi Krishna

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

All Works

6 of 6 papers shown
1.
Zhao, Sicheng, Xiangyu Yue, Chuang Lin, et al.. (2021). Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation. IEEE Transactions on Cybernetics. 52(10). 10000–10013. 15 indexed citations
2.
Zhao, Sicheng, Jiang Guo, Xiangyu Yue, et al.. (2021). Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources. 541–552. 15 indexed citations
3.
Zhao, Sicheng, Xiangyu Yue, Shanghang Zhang, et al.. (2020). A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. arXiv (Cornell University). 15 indexed citations
4.
Krishna, Ravi, Norman Mu, & Kurt Keutzer. (2020). Applying Text Analytics to the Mind-section Literature of the Tibetan Tradition of the Great Perfection. ACM Transactions on Asian and Low-Resource Language Information Processing. 20(2). 1–32. 1 indexed citations
5.
Zhao, Sicheng, Xiangyu Yue, Shanghang Zhang, et al.. (2020). A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. IEEE Transactions on Neural Networks and Learning Systems. 33(2). 473–493. 242 indexed citations
6.
Zhao, Sicheng, Chuang Lin, Pengfei Xu, et al.. (2019). CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting Image Emotions. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 2620–2627. 41 indexed citations

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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2026