Weihua Hu
- Artificial Intelligence top 2%
- Atmospheric Science top 5%
- Computer Vision and Pattern Recognition top 2%
- Computer Networks and Communications top 5%
- Global and Planetary Change top 5%
- Topics
- Atmospheric chemistry and aerosols (6 papers)Software-Defined Networks and 5G (5 papers)Atmospheric Ozone and Climate (5 papers)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Weihua Hu
36 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 735
- Atmospheric Science 409
- Computer Vision and Pattern Recognition 395
- Computer Networks and Communications 343
- Global and Planetary Change 325
Countries citing papers authored by Weihua Hu
This map shows the geographic impact of Weihua Hu'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 Weihua Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weihua Hu more than expected).
Fields of papers citing papers by Weihua Hu
This network shows the impact of papers produced by Weihua Hu. 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 Weihua Hu. The network helps show where Weihua Hu may publish in the future.
Co-authorship network of co-authors of Weihua Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Weihua Hu. A scholar is included among the top collaborators of Weihua Hu 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 Weihua Hu. Weihua Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Learning skillful medium-range global weather forecastingbreakdown → | 535 |
| 3 | 2 | |
| 4 | OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs. | 1 |
| 5 | Pre-training Graph Neural Networks. | 5 |
| 6 | 60 | |
| 7 | Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labelsbreakdown → | 664 |
| 8 | Learning from Complementary Labels | 15 |
| 9 | 21 | |
| 10 | 2 | |
| 11 | 21 | |
| 12 | 39 | |
| 13 | Mobileflow: Toward software-defined mobile networksbreakdown → | 253 |
| 14 | 0 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | 3 | |
| 18 | APPLICATION OF MARKOV MODEL IN EARTHQUAKE DAMAGE PREDICTION OF BUILDINGS | 0 |
| 19 | 14 | |
| 20 | Springtime photochemical ozone production observed in the upper troposphere over East Asia | 1 |
About Weihua Hu
Weihua Hu is a scholar working on Computer Networks and Communications, Atmospheric Science and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 1.9k indexed citations. Recurring topics across this work include Atmospheric chemistry and aerosols (6 papers), Software-Defined Networks and 5G (5 papers) and Atmospheric Ozone and Climate (5 papers). The work is most often cited by research in Artificial Intelligence (735 citations), Atmospheric Science (409 citations) and Computer Vision and Pattern Recognition (395 citations). Weihua Hu has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Gang Niu, Masashi Sugiyama, Yan Wang, Kostas Pentikousis, Ivor W. Tsang, Bo Han, Miao Xu, Xingrui Yu, Quanming Yao and Shakir Mohamed. Their work appears in journals such as Science, Journal of Geophysical Research Atmospheres and Geophysical Research Letters.
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.