Philipp Seidl
Impact in
- Anesthesiology and Pain Medicine top 10%
- Airway Management and Intubation Techniques
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- Computational Drug Discovery Methods
Papers in
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- Machine Learning in Materials Science 3
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- Machine Learning in Bioinformatics 1
- Protein Structure and Dynamics 1
- Co-authors
- Sepp Hochreiter (6 shared papers)Günter Klambauer (3 shared papers)Hinnerk Wulf (1 shared paper)Clemens Kill (1 shared paper)Joachim Riße (1 shared paper)Thorsten Steinfeldt (1 shared paper)Marwin Segler (2 shared papers)Johannes M. Lehner (1 shared paper)
- Journals
- European Journal of Emergency Medicine (1 paper)Faraday Discussions (1 paper)Journal of Emergency Medicine (1 paper)Anesthesia & Analgesia (1 paper)Journal of Chemical Information and Modeling (1 paper)
- Partner nations
- AustriaGermanyUnited States
In The Last Decade
Philipp Seidl
10 papers receiving 210 citations
Peers
Comparison fields: 5 of 59
- Anesthesiology and Pain Medicine 38
- Computational Theory and Mathematics 38
- Artificial Intelligence 74
- Computer Vision and Pattern Recognition 33
- Health Informatics 2
Countries citing papers authored by Philipp Seidl
This map shows the geographic impact of Philipp Seidl'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 Philipp Seidl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Seidl more than expected).
Fields of papers citing papers by Philipp Seidl
This network shows the impact of papers produced by Philipp Seidl. 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 Philipp Seidl. The network helps show where Philipp Seidl may publish in the future.
Co-authors
The 25 scholars most cited alongside Philipp Seidl, 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 | Hopfield Networks is All You Need | 2021 | 77 |
| 2 | 2022 | 49 | |
| 3 | 2013 | 45 | |
| 4 | 2024 | 22 | |
| 5 | 2023 | 12 | |
| 6 | 2024 | 3 | |
| 7 | 2020 | 3 | |
| 8 | 2022 | 2 | |
| 9 | Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. | 2021 | 1 |
| 10 | 2024 | 1 |
About Philipp Seidl
Philipp Seidl is a scholar working on Materials Chemistry, Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics and Cardiology and Cardiovascular Medicine, having authored 10 papers that have together received 215 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (3 papers), Computational Drug Discovery Methods (2 papers), Stock Market Forecasting Methods (1 paper), Atrial Fibrillation Management and Outcomes (1 paper), Airway Management and Intubation Techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Neural Networks and Applications (1 paper) and Protein Structure and Dynamics (1 paper). The work is most often cited by research in Anesthesiology and Pain Medicine (38 citations), Computational Theory and Mathematics (38 citations), Artificial Intelligence (74 citations), Computer Vision and Pattern Recognition (33 citations) and Health Informatics (2 citations). Philipp Seidl has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Sepp Hochreiter, Günter Klambauer, Hinnerk Wulf, Clemens Kill, Joachim Riße, Thorsten Steinfeldt, Marwin Segler, Johannes M. Lehner, Jonas Verhoeven and Hubert Ramsauer. Their work appears in journals such as European Journal of Emergency Medicine, Faraday Discussions, Journal of Emergency Medicine, Anesthesia & Analgesia and Journal of Chemical Information and Modeling.
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.