Yida Wang
Impact in
- Computational Mathematics top 10%
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
-
- Advanced Neural Network Applications 11
-
- Natural Language Processing Techniques 5
- Topic Modeling 5
- Neural Networks and Applications 3
- Co-authors
- Jiang-Ming Yang (2 shared papers)Rui Cai (2 shared papers)Mu Li (5 shared papers)Wei Lai (1 shared paper)Lei Zhang (1 shared paper)Jonathan D. Cohen (3 shared papers)Yao Wang (2 shared papers)Wei‐Ying Ma (1 shared paper)
- Journals
- The VLDB Journal (1 paper)The Science of The Total Environment (1 paper)Experimental Hematology and Oncology (1 paper)Materials Today Chemistry (1 paper)Journal of Experimental & Clinical Cancer Research (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Yida Wang
41 papers receiving 413 citations
Peers
Comparison fields: 5 of 84
- Computational Mathematics 10
- Hardware and Architecture 67
- Computer Vision and Pattern Recognition 121
- Artificial Intelligence 152
- Information Systems 99
Countries citing papers authored by Yida Wang
This map shows the geographic impact of Yida 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 Yida Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yida Wang more than expected).
Fields of papers citing papers by Yida Wang
This network shows the impact of papers produced by Yida 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 Yida Wang. The network helps show where Yida Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yida Wang, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 52 | |
| 2 | 2009 | 43 | |
| 3 | 2020 | 42 | |
| 4 | Optimizing CNN model inference on CPUs | 2019 | 26 |
| 5 | Ansor: Generating high-performance tensor programs for deep learning | 2020 | 24 |
| 6 | 2023 | 23 | |
| 7 | 2019 | 21 | |
| 8 | 2015 | 20 | |
| 9 | 2024 | 18 | |
| 10 | 2022 | 18 | |
| 11 | 2021 | 16 | |
| 12 | 2022 | 13 | |
| 13 | 2022 | 12 | |
| 14 | 2022 | 11 | |
| 15 | 2016 | 11 | |
| 16 | 2015 | 10 | |
| 17 | 2021 | 8 | |
| 18 | 2006 | 7 | |
| 19 | 2025 | 6 | |
| 20 | 2021 | 6 |
About Yida Wang
Yida Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Hardware and Architecture, Cognitive Neuroscience and Computer Networks and Communications, having authored 45 papers that have together received 438 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (11 papers), Parallel Computing and Optimization Techniques (6 papers), Natural Language Processing Techniques (5 papers), Topic Modeling (5 papers), Functional Brain Connectivity Studies (5 papers), Data Management and Algorithms (3 papers), Land Use and Ecosystem Services (3 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Computational Mathematics (10 citations), Hardware and Architecture (67 citations), Computer Vision and Pattern Recognition (121 citations), Artificial Intelligence (152 citations) and Information Systems (99 citations). Yida Wang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Jiang-Ming Yang, Rui Cai, Mu Li, Wei Lai, Lei Zhang, Jonathan D. Cohen, Yao Wang, Lei Zhang, Wei‐Ying Ma and Nicholas B. Turk‐Browne. Their work appears in journals such as The VLDB Journal, The Science of The Total Environment, Experimental Hematology and Oncology, Materials Today Chemistry and Journal of Experimental & Clinical Cancer Research.
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.