Will Y. Zou
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Biomedical Engineering
- Human-Computer Interaction top 5%
- Signal Processing top 10%
- Co-authors
- Andrew Y. NgQuoc V. LeSerena YeungRichard SocherDaniel CerChristopher D. ManningShenghuo ZhuKai Yu
- Topics
- Advanced Image and Video Retrieval Techniques (3 papers)Cognitive and developmental aspects of mathematical skills (2 papers)Sparse and Compressive Sensing Techniques (1 paper)
- Journals
- Cognitive ScienceDevelopmental ScienceNeural Information Processing Systems
- Partner nations
- United StatesChinaItaly
In The Last Decade
Will Y. Zou
8 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 723
- Artificial Intelligence 647
- Biomedical Engineering 167
- Human-Computer Interaction 78
- Signal Processing 59
Countries citing papers authored by Will Y. Zou
This map shows the geographic impact of Will Y. Zou'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 Will Y. Zou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Y. Zou more than expected).
Fields of papers citing papers by Will Y. Zou
This network shows the impact of papers produced by Will Y. Zou. 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 Will Y. Zou. The network helps show where Will Y. Zou may publish in the future.
Co-authorship network of co-authors of Will Y. Zou
This figure shows the co-authorship network connecting the top 25 collaborators of Will Y. Zou. A scholar is included among the top collaborators of Will Y. Zou 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 Will Y. Zou. Will Y. Zou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 37 | |
| 2 | 13 | |
| 3 | 42 | |
| 4 | Bilingual Word Embeddings for Phrase-Based Machine Translationbreakdown → | 307 |
| 5 | Progressive Development of the Number Sense in a Deep Neural Network. | 2 |
| 6 | Deep Learning of Invariant Features via Simulated Fixations in Video | 87 |
| 7 | Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysisbreakdown → | 658 |
| 8 | An ADMM Solution to the Sparse Coding Problem | 3 |
About Will Y. Zou
Will Y. Zou is a scholar working on Computer Vision and Pattern Recognition, Statistics and Probability and Artificial Intelligence, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Cognitive and developmental aspects of mathematical skills (2 papers) and Sparse and Compressive Sensing Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (723 citations), Artificial Intelligence (647 citations) and Human-Computer Interaction (78 citations). Will Y. Zou has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Andrew Y. Ng, Quoc V. Le, Serena Yeung, Richard Socher, Daniel Cer, Christopher D. Manning, Shenghuo Zhu, Kai Yu, James L. McClelland and Alberto Testolin. Their work appears in journals such as Cognitive Science, Developmental Science and Neural Information Processing Systems.
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.