Rose Yu
Impact in
- Computational Mathematics top 2%
- Tensor decomposition and applications
-
- Complex Network Analysis Techniques
Papers in ⓘ
-
- Computational Physics and Python Applications 4
- Gaussian Processes and Bayesian Inference 4
- Anomaly Detection Techniques and Applications 3
-
- Model Reduction and Neural Networks 6
- Complex Network Analysis Techniques 5
- Co-authors
- Yan Liu (7 shared papers)Xinran He (2 shared papers)Paul Wong (4 shared papers)Albert-Ĺaszló Barabási (3 shared papers)Rui Wang (1 shared paper)Anima Anandkumar (1 shared paper)Yisong Yue (2 shared papers)Stephan Zheng (2 shared papers)
- Journals
- Nature Communications (3 papers)Nature Machine Intelligence (2 papers)Proceedings of the National Academy of Sciences (1 paper)JMIR Rehabilitation and Assistive Technologies (1 paper)American Journal of Respiratory Cell and Molecular Biology (1 paper)
- Partner nations
- United StatesHong KongUnited Kingdom
In The Last Decade
Rose Yu
41 papers receiving 614 citations
Peers
Comparison fields: 5 of 129
- Computational Mathematics 64
- Statistical and Nonlinear Physics 91
- Artificial Intelligence 216
- Signal Processing 69
- Transportation 33
Countries citing papers authored by Rose Yu
This map shows the geographic impact of Rose Yu'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 Rose Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rose Yu more than expected).
Fields of papers citing papers by Rose Yu
This network shows the impact of papers produced by Rose Yu. 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 Rose Yu. The network helps show where Rose Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Rose Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 76 | |
| 2 | 2016 | 63 | |
| 3 | 2015 | 62 | |
| 4 | Long-term Forecasting using Tensor-Train RNNs | 2017 | 55 |
| 5 | Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. | 2017 | 44 |
| 6 | Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams | 2015 | 37 |
| 7 | 2023 | 36 | |
| 8 | 2021 | 35 | |
| 9 | 2014 | 30 | |
| 10 | 2024 | 30 | |
| 11 | 2019 | 25 | |
| 12 | 2017 | 22 | |
| 13 | Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology | 2019 | 14 |
| 14 | 2016 | 14 | |
| 15 | 2021 | 13 | |
| 16 | 2023 | 10 | |
| 17 | Tensor Regression Meets Gaussian Processes | 2017 | 8 |
| 18 | 2022 | 7 | |
| 19 | Learning Disentangled Representations of Videos with Missing Data | 2020 | 5 |
| 20 | 2021 | 5 |
About Rose Yu
Rose Yu is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Molecular Biology and Computational Mathematics, having authored 42 papers that have together received 638 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (6 papers), Complex Network Analysis Techniques (5 papers), Tensor decomposition and applications (4 papers), Computational Physics and Python Applications (4 papers), Gaussian Processes and Bayesian Inference (4 papers), Network Security and Intrusion Detection (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Human-Animal Interaction Studies (3 papers). The work is most often cited by research in Computational Mathematics (64 citations), Statistical and Nonlinear Physics (91 citations), Artificial Intelligence (216 citations), Signal Processing (69 citations) and Transportation (33 citations). Rose Yu has collaborated with scholars based in United States, Hong Kong and United Kingdom. Frequent co-authors include Yan Liu, Xinran He, Paul Wong, Albert-Ĺaszló Barabási, Rui Wang, Anima Anandkumar, Yisong Yue, Stephan Zheng, Yan Liu and Ching‐Yung Lin. Their work appears in journals such as Nature Communications, Nature Machine Intelligence, Proceedings of the National Academy of Sciences, JMIR Rehabilitation and Assistive Technologies and American Journal of Respiratory Cell and Molecular Biology.
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.