Günter Klambauer
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods 21
- Biophysics top 1%
- Cell Image Analysis Techniques 6
- Health Informatics top 5%
- Molecular Biology top 5%
- Protein Structure and Dynamics 7
- Materials Chemistry top 5%
- Machine Learning in Materials Science 14
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- Hydrological Forecasting Using AI 6
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- Hydrology and Watershed Management Studies 6
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- Flood Risk Assessment and Management 6
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- Genomic variations and chromosomal abnormalities 4
- Co-authors
- Sepp HochreiterAndreas MayrThomas UnterthinerDjork-Arné ClevertJörg K. WegnerKristina PreuerAndreas BenderRichard P. Lewis
- Journals
- Nucleic Acids Research (3 papers)Nature Communications (1 paper)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- AustriaUnited StatesBelgium
In The Last Decade
Günter Klambauer
44 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Computational Theory and Mathematics 1.6k
- Biophysics 278
- Health Informatics 45
- Molecular Biology 1.5k
- Materials Chemistry 758
Countries citing papers authored by Günter Klambauer
This map shows the geographic impact of Günter Klambauer'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 Günter Klambauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Günter Klambauer more than expected).
Fields of papers citing papers by Günter Klambauer
This network shows the impact of papers produced by Günter Klambauer. 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 Günter Klambauer. The network helps show where Günter Klambauer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Günter Klambauer, 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 | 2025 | 0 | |
| 2 | 2023 | 24 | |
| 3 | 2022 | 104 | |
| 4 | 2022 | 50 | |
| 5 | 2021 | 13 | |
| 6 | 2021 | 1 | |
| 7 | Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. | 2021 | 1 |
| 8 | 2021 | 35 | |
| 9 | 2020 | 102 | |
| 10 | 2020 | 29 | |
| 11 | Towards the quantification of uncertainty for deep learning based rainfall-runoff models | 2019 | 1 |
| 12 | 2019 | 86 | |
| 13 | 2019 | 18 | |
| 14 | Fréchet ChemblNet Distance: A metric for generative models for molecules. | 2018 | 2 |
| 15 | Human-level Protein Localization with Convolutional Neural Networks | 2018 | 5 |
| 16 | Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields | 2018 | 6 |
| 17 | 2018 | 140 | |
| 18 | 2017 | 24 | |
| 19 | 2016 | 119 | |
| 20 | 2015 | 63 |
About Günter Klambauer
Günter Klambauer is a scholar working on Computational Theory and Mathematics, Biophysics and Water Science and Technology, having authored 45 papers that have together received 3.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (21 papers), Machine Learning in Materials Science (14 papers), Protein Structure and Dynamics (7 papers), Hydrological Forecasting Using AI (6 papers), Hydrology and Watershed Management Studies (6 papers), Flood Risk Assessment and Management (6 papers), Cell Image Analysis Techniques (6 papers) and Genomic variations and chromosomal abnormalities (4 papers). The work is most often cited by research in Computational Theory and Mathematics (1.6k citations), Biophysics (278 citations) and Health Informatics (45 citations). Günter Klambauer has collaborated with scholars based in Austria, United States and Belgium. Frequent co-authors include Sepp Hochreiter, Andreas Mayr, Thomas Unterthiner, Djork-Arné Clevert, Jörg K. Wegner, Kristina Preuer, Andreas Bender, Richard P. Lewis, Krishna C. Bulusu and Hugo Ceulemans. Their work appears in journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.
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.