Jens Behrmann
Impact in
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- Mass Spectrometry Techniques and Applications
- Advanced Proteomics Techniques and Applications
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- Adversarial Robustness in Machine Learning
- AI in cancer detection
Papers in
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- Neural Networks and Applications 2
- Adversarial Robustness in Machine Learning 1
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- Metabolomics and Mass Spectrometry Studies 1
- Molecular Biology Techniques and Applications 1
- Co-authors
- Tobias Boskamp (3 shared papers)Jörg Kriegsmann (2 shared papers)Rita Casadonte (2 shared papers)Christian Etmann (1 shared paper)Joern-Henrik Jacobsen (3 shared papers)Ricky T. Q. Chen (2 shared papers)David Duvenaud (2 shared papers)Will Grathwohl (1 shared paper)
- Journals
- Bioinformatics (1 paper)PROTEOMICS - CLINICAL APPLICATIONS (1 paper)Analytical Chemistry (1 paper)Neural Information Processing Systems (1 paper)Medical Entomology and Zoology (1 paper)
- Partner nations
- GermanyCanadaUnited States
In The Last Decade
Jens Behrmann
8 papers receiving 171 citations
Peers
Comparison fields: 5 of 53
- Spectroscopy 52
- Artificial Intelligence 64
- Biophysics 11
- Computer Vision and Pattern Recognition 39
- Computational Mathematics 1
Countries citing papers authored by Jens Behrmann
This map shows the geographic impact of Jens Behrmann'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 Jens Behrmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jens Behrmann more than expected).
Fields of papers citing papers by Jens Behrmann
This network shows the impact of papers produced by Jens Behrmann. 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 Jens Behrmann. The network helps show where Jens Behrmann may publish in the future.
Co-authors
The 24 scholars most cited alongside Jens Behrmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 92 | |
| 2 | Invertible Residual Networks | 2019 | 39 |
| 3 | Residual Flows for Invertible Generative Modeling | 2019 | 18 |
| 4 | 2022 | 13 | |
| 5 | Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations | 2020 | 8 |
| 6 | 2024 | 4 | |
| 7 | On the Invertibility of Invertible Neural Networks | 2019 | 1 |
| 8 | Zur Klassifikation äquivarianter Vektorraumbündel über Toruseinbettungen | 1986 | 1 |
About Jens Behrmann
Jens Behrmann is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Signal Processing and Spectroscopy, having authored 8 papers that have together received 176 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Music and Audio Processing (2 papers), Neural Networks and Applications (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Metabolomics and Mass Spectrometry Studies (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Molecular Biology Techniques and Applications (1 paper). The work is most often cited by research in Spectroscopy (52 citations), Artificial Intelligence (64 citations), Biophysics (11 citations), Computer Vision and Pattern Recognition (39 citations) and Computational Mathematics (1 citation). Jens Behrmann has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Tobias Boskamp, Jörg Kriegsmann, Rita Casadonte, Christian Etmann, Joern-Henrik Jacobsen, Ricky T. Q. Chen, David Duvenaud, Will Grathwohl, Nicholas Carlini and Florian Tramèr. Their work appears in journals such as Bioinformatics, PROTEOMICS - CLINICAL APPLICATIONS, Analytical Chemistry, Neural Information Processing Systems and Medical Entomology and Zoology.
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.