David J. Schwab
- Molecular Biology
- Cellular and Molecular Neuroscience top 10%
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 10%
- Genetics
- Co-authors
- Pankaj MehtaE. Miles StoudenmireNed S. WingreenJoshua D. RabinowitzGautam B. AwatramaniStuart TrenholmAmanda J. McLaughlinIlya Nemenman
- Topics
- Neural dynamics and brain function (9 papers)Photoreceptor and optogenetics research (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Partner nations
- United StatesCanadaIsrael
In The Last Decade
David J. Schwab
43 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 128
- Molecular Biology 528
- Cellular and Molecular Neuroscience 253
- Cognitive Neuroscience 230
- Artificial Intelligence 136
- Genetics 103
Countries citing papers authored by David J. Schwab
This map shows the geographic impact of David J. Schwab'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 J. Schwab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Schwab more than expected).
Fields of papers citing papers by David J. Schwab
This network shows the impact of papers produced by David J. Schwab. 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 J. Schwab. The network helps show where David J. Schwab may publish in the future.
Co-authorship network of co-authors of David J. Schwab
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Schwab. A scholar is included among the top collaborators of David J. Schwab 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 David J. Schwab. David J. Schwab is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs | 2 |
| 3 | Information-bottleneck renormalization group for self-supervised representation learning | 2 |
| 4 | Learning Optimal Representations with the Decodable Information Bottleneck | 0 |
| 5 | Conjugate unscented transformation based semi-analytic approach for uncertainty characterization of angles-only initial orbit determination algorithms | 1 |
| 6 | The renormalization group and information bottleneck: a unified framework | 0 |
| 7 | Supervised Learning with Tensor Networks | 103 |
| 8 | 62 | |
| 9 | 52 | |
| 10 | 24 | |
| 11 | 59 | |
| 12 | 55 | |
| 13 | 35 | |
| 14 | 38 | |
| 15 | 48 | |
| 16 | 193 | |
| 17 | 2 | |
| 18 | 28 | |
| 19 | 8 | |
| 20 | 24 |
About David J. Schwab
David J. Schwab is a scholar working on Computational Mathematics, Cognitive Neuroscience and Statistics, Probability and Uncertainty, having authored 46 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (9 papers), Photoreceptor and optogenetics research (6 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computational Mathematics (41 citations), Cellular and Molecular Neuroscience (253 citations) and Cognitive Neuroscience (230 citations). David J. Schwab has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Pankaj Mehta, E. Miles Stoudenmire, Ned S. Wingreen, Joshua D. Rabinowitz, Gautam B. Awatramani, Stuart Trenholm, Amanda J. McLaughlin, Ilya Nemenman, Santhosh Sethuramanujam and Javad Noorbakhsh. Their work appears in journals such as Physical Review Letters, Nature Communications and Neuron.
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.