David Bau
Impact in
- Computer Science Applications top 0.5%
- Teaching and Learning Programming
- Computational Mathematics top 5%
Papers in
-
- Explainable Artificial Intelligence (XAI) 7
- Adversarial Robustness in Machine Learning 5
-
- Generative Adversarial Networks and Image Synthesis 9
- Multimodal Machine Learning Applications 5
- Co-authors
- Lloyd N. Trefethen (2 shared papers)Antonio Torralba (13 shared papers)Bolei Zhou (6 shared papers)Jeff Gray (2 shared papers)Franklyn Turbak (2 shared papers)Caitlin Kelleher (2 shared papers)Josh Sheldon (2 shared papers)Jun-Yan Zhu (5 shared papers)
- Journals
- Journal of Vision (1 paper)International Journal of Child-Computer Interaction (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Communications of the ACM (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesMexicoHong Kong
In The Last Decade
David Bau
42 papers receiving 4.0k citations
David Bau's Hit Papers
Peers
Comparison fields: 5 of 165
- Computer Science Applications 528
- Computational Mathematics 44
- Numerical Analysis 247
- Computer Vision and Pattern Recognition 877
- Artificial Intelligence 1.1k
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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Numerical Linear Algebra Hit paper breakdown → | 1997 | 2334 |
| 2 | Learnable programming Hit paper breakdown → | 2017 | 248 |
| 3 | 2020 | 221 | |
| 4 | 2020 | 216 | |
| 5 | 2018 | 190 | |
| 6 | 2017 | 152 | |
| 7 | 2018 | 151 | |
| 8 | 2015 | 121 | |
| 9 | 2023 | 80 | |
| 10 | Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning | 2018 | 70 |
| 11 | 2020 | 60 | |
| 12 | 2008 | 38 | |
| 13 | 2024 | 37 | |
| 14 | Droplet, a blocks-based editor for text code | 2015 | 36 |
| 15 | 1995 | 28 | |
| 16 | 2001 | 24 | |
| 17 | 2022 | 21 | |
| 18 | 2024 | 12 | |
| 19 | 2022 | 12 | |
| 20 | 2024 | 10 |
About David Bau
David Bau is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications, Hardware and Architecture and Information Systems and Management, having authored 44 papers that have together received 4.2k indexed citations. Recurring topics across this work include Teaching and Learning Programming (11 papers), Generative Adversarial Networks and Image Synthesis (9 papers), Explainable Artificial Intelligence (XAI) (7 papers), Adversarial Robustness in Machine Learning (5 papers), Multimodal Machine Learning Applications (5 papers), Scientific Computing and Data Management (5 papers), Embedded Systems Design Techniques (4 papers) and Cell Image Analysis Techniques (4 papers). The work is most often cited by research in Computer Science Applications (528 citations), Computational Mathematics (44 citations), Numerical Analysis (247 citations), Computer Vision and Pattern Recognition (877 citations) and Artificial Intelligence (1.1k citations). David Bau has collaborated with scholars based in United States, Mexico and Hong Kong. Frequent co-authors include Lloyd N. Trefethen, Antonio Torralba, Bolei Zhou, Jeff Gray, Franklyn Turbak, Caitlin Kelleher, Josh Sheldon, Jun-Yan Zhu, Ser-Nam Lim and Lucy Chai. Their work appears in journals such as Journal of Vision, International Journal of Child-Computer Interaction, IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM 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.