David Pfau
Impact in
- Biophysics top 2%
- Advanced Fluorescence Microscopy Techniques
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
Papers in ⓘ
-
- Gaussian Processes and Bayesian Inference 4
- Neural Networks and Applications 3
- Bayesian Methods and Mixture Models 3
- Machine Learning and Algorithms 2
- Co-authors
- Eftychios A. Pnevmatikakis (2 shared papers)Liam Paninski (3 shared papers)Luke Metz (1 shared paper)Jascha Sohl‐Dickstein (1 shared paper)Ben Poole (1 shared paper)Yuanjun Gao (1 shared paper)Clay Lacefield (1 shared paper)Thomas R. Reardon (1 shared paper)
- Journals
- American Journal of Roentgenology (2 papers)Science (2 papers)Nature Communications (1 paper)Abdominal Radiology (1 paper)Physics of Plasmas (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
David Pfau
25 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Biophysics 184
- Cognitive Neuroscience 406
- Cellular and Molecular Neuroscience 375
- Acoustics and Ultrasonics 9
- Sensory Systems 47
Countries citing papers authored by David Pfau
This map shows the geographic impact of David Pfau'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 Pfau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Pfau more than expected).
Fields of papers citing papers by David Pfau
This network shows the impact of papers produced by David Pfau. 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 Pfau. The network helps show where David Pfau may publish in the future.
Co-authors
The 25 scholars most cited alongside David Pfau, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data Hit paper breakdown → | 2016 | 608 |
| 2 | Pushing the frontiers of density functionals by solving the fractional electron problem Hit paper breakdown → | 2021 | 243 |
| 3 | 2016 | 175 | |
| 4 | 2023 | 63 | |
| 5 | 2023 | 47 | |
| 6 | 2016 | 44 | |
| 7 | 2013 | 31 | |
| 8 | Robust learning of low-dimensional dynamics from large neural ensembles | 2013 | 27 |
| 9 | 2024 | 19 | |
| 10 | 2021 | 14 | |
| 11 | Probabilistic Deterministic Infinite Automata | 2010 | 11 |
| 12 | 2019 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2019 | 9 | |
| 15 | 2010 | 8 | |
| 16 | 2024 | 7 | |
| 17 | Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning | 2015 | 6 |
| 18 | 2024 | 6 | |
| 19 | 2020 | 4 | |
| 20 | 2012 | 3 |
About David Pfau
David Pfau is a scholar working on Biophysics, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics and Statistical and Nonlinear Physics, having authored 26 papers that have together received 1.4k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), Advanced Chemical Physics Studies (4 papers), Gaussian Processes and Bayesian Inference (4 papers), Neural Networks and Applications (3 papers), Lung Cancer Treatments and Mutations (3 papers), Bayesian Methods and Mixture Models (3 papers), Colorectal Cancer Treatments and Studies (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Biophysics (184 citations), Cognitive Neuroscience (406 citations), Cellular and Molecular Neuroscience (375 citations), Acoustics and Ultrasonics (9 citations) and Sensory Systems (47 citations). David Pfau has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Eftychios A. Pnevmatikakis, Liam Paninski, Luke Metz, Jascha Sohl‐Dickstein, Ben Poole, Yuanjun Gao, Clay Lacefield, Thomas R. Reardon, Daniel Soudry and Thomas M. Jessell. Their work appears in journals such as American Journal of Roentgenology, Science, Nature Communications, Abdominal Radiology and Physics of Plasmas.
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.