Yulai Cong
About
In The Last Decade
Yulai Cong
21 papers receiving 297 citations
Peers
Comparison fields: 5 of 71
- Computer Vision and Pattern Recognition 111
- Artificial Intelligence 111
- Aerospace Engineering 107
- Biomedical Engineering 38
- Computational Mechanics 31
Countries citing papers authored by Yulai Cong
This map shows the geographic impact of Yulai Cong'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 Yulai Cong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yulai Cong more than expected).
Fields of papers citing papers by Yulai Cong
This network shows the impact of papers produced by Yulai Cong. 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 Yulai Cong. The network helps show where Yulai Cong may publish in the future.
Co-authorship network of co-authors of Yulai Cong
This figure shows the co-authorship network connecting the top 25 collaborators of Yulai Cong. A scholar is included among the top collaborators of Yulai Cong 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 Yulai Cong. Yulai Cong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 7 | |
| 6 | 2 | |
| 7 | 14 | |
| 8 | On Leveraging Pretrained GANs for Limited-Data Generation | 10 |
| 9 | On Leveraging Pretrained GANs for Generation with Limited Data | 3 |
| 10 | 4 | |
| 11 | 33 | |
| 12 | Deep latent dirichlet allocation with topic-layer-adaptive stochastic gradient riemannian MCMC | 5 |
| 13 | 27 | |
| 14 | Augmentable gamma belief networks | 26 |
| 15 | 41 | |
| 16 | 20 | |
| 17 | 20 | |
| 18 | 2 | |
| 19 | 5 | |
| 20 | 62 |
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.