David Bau
Impact in
- Computer Science Applications top 0.5%
- Teaching and Learning Programming
- Computational Mathematics top 5%
Papers in
-
- Generative Adversarial Networks and Image Synthesis 7
- Multimodal Machine Learning Applications 4
-
- Explainable Artificial Intelligence (XAI) 5
- Natural Language Processing Techniques 3
- Co-authors
- Lloyd N. Trefethen (2 shared papers)Antonio Torralba (10 shared papers)Bolei Zhou (4 shared papers)Franklyn Turbak (2 shared papers)Caitlin Kelleher (2 shared papers)Jeff Gray (2 shared papers)Josh Sheldon (2 shared papers)Jun-Yan Zhu (5 shared papers)
- Journals
- Journal of Vision (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)ACM Transactions on Graphics (1 paper)Cognitive Systems Research (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesMexicoUnited Kingdom
In The Last Decade
David Bau
34 papers receiving 3.1k citations
David Bau's Hit Papers
Peers
Comparison fields: 5 of 163
- Computer Science Applications 394
- Computational Mathematics 39
- Numerical Analysis 220
- Computer Vision and Pattern Recognition 527
- Computational Theory and Mathematics 409
Countries citing papers authored by David Bau
This map shows the geographic impact of David Bau'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 David Bau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Bau more than expected).
Fields of papers citing papers by David Bau
This network shows the impact of papers produced by David Bau. 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 David Bau. The network helps show where David Bau may publish in the future.
Co-authors
The 25 scholars most cited alongside David Bau, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Numerical Linear Algebra Hit paper breakdown → | 1997 | 2119 |
| 2 | 2020 | 207 | |
| 3 | 2017 | 188 | |
| 4 | 2018 | 165 | |
| 5 | 2017 | 113 | |
| 6 | 2015 | 77 | |
| 7 | 2020 | 58 | |
| 8 | Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning | 2018 | 56 |
| 9 | 2023 | 47 | |
| 10 | Droplet, a blocks-based editor for text code | 2015 | 34 |
| 11 | 2008 | 34 | |
| 12 | 2024 | 15 | |
| 13 | 2022 | 13 | |
| 14 | 2022 | 12 | |
| 15 | 2024 | 8 | |
| 16 | 2022 | 7 | |
| 17 | 2014 | 6 | |
| 18 | Comparison of Spherical Harmonics and Nearest-Neighbor based Interpolation of Head-Related Transfer Functions | 2020 | 6 |
| 19 | 2015 | 5 | |
| 20 | 2019 | 5 |
About David Bau
David Bau is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Science Applications, Information Systems and Management and Signal Processing, having authored 36 papers that have together received 3.2k indexed citations. Recurring topics across this work include Teaching and Learning Programming (10 papers), Generative Adversarial Networks and Image Synthesis (7 papers), Scientific Computing and Data Management (5 papers), Explainable Artificial Intelligence (XAI) (5 papers), Cell Image Analysis Techniques (4 papers), Multimodal Machine Learning Applications (4 papers), Embedded Systems Design Techniques (4 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Computer Science Applications (394 citations), Computational Mathematics (39 citations), Numerical Analysis (220 citations), Computer Vision and Pattern Recognition (527 citations) and Computational Theory and Mathematics (409 citations). David Bau has collaborated with scholars based in United States, Mexico and United Kingdom. Frequent co-authors include Lloyd N. Trefethen, Antonio Torralba, Bolei Zhou, Franklyn Turbak, Caitlin Kelleher, Jeff Gray, Josh Sheldon, Jun-Yan Zhu, Aude Oliva and Hendrik Strobelt. Their work appears in journals such as Journal of Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics, Cognitive Systems Research and Proceedings of the National Academy of Sciences.
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.