Yali Wang
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 1%
- Biomedical Engineering top 10%
- Media Technology top 1%
- Electrical and Electronic Engineering
- Co-authors
- Yu QiaoPeiqin ZhuangWenbin DuJunjun HeHao ChenLei ZhouZhongying DengGuoyou Wang
- Topics
- Human Pose and Action Recognition (25 papers)Multimodal Machine Learning Applications (24 papers)Domain Adaptation and Few-Shot Learning (17 papers)
In The Last Decade
Yali Wang
138 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Computer Vision and Pattern Recognition 2.1k
- Artificial Intelligence 1.2k
- Biomedical Engineering 301
- Media Technology 260
- Electrical and Electronic Engineering 196
Countries citing papers authored by Yali Wang
This map shows the geographic impact of Yali Wang'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 Yali Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yali Wang more than expected).
Fields of papers citing papers by Yali Wang
This network shows the impact of papers produced by Yali Wang. 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 Yali Wang. The network helps show where Yali Wang may publish in the future.
Co-authorship network of co-authors of Yali Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Yali Wang. A scholar is included among the top collaborators of Yali Wang 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 Yali Wang. Yali Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 33 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 12 | |
| 11 | 0 | |
| 12 | 11 | |
| 13 | 26 | |
| 14 | 2 | |
| 15 | Sequential Inference for Deep Gaussian Process | 6 |
| 16 | Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations | 21 |
| 17 | A KNN based kalman filter Gaussian process regression | 9 |
| 18 | 69 | |
| 19 | A Marginalized Particle Gaussian Process Regression | 6 |
| 20 | 58 |
About Yali Wang
Yali Wang is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics and Artificial Intelligence, having authored 152 papers that have together received 3.4k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (25 papers), Multimodal Machine Learning Applications (24 papers) and Domain Adaptation and Few-Shot Learning (17 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Artificial Intelligence (1.2k citations) and Media Technology (260 citations). Yali Wang has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include Yu Qiao, Peiqin Zhuang, Wenbin Du, Junjun He, Hao Chen, Lei Zhou, Zhongying Deng, Guoyou Wang, Hongsheng Li and Limin Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Power Sources and Langmuir.
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.