Philipp Renz
Impact in
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- Computational Drug Discovery Methods
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- Anesthesia and Sedative Agents
Papers in
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- Computational Drug Discovery Methods 5
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- Machine Learning in Materials Science 5
- Co-authors
- Günter Klambauer (5 shared papers)Sepp Hochreiter (4 shared papers)Jörg K. Wegner (3 shared papers)Dries Van Rompaey (1 shared paper)Jonas Verhoeven (2 shared papers)Natalia Dyubankova (2 shared papers)Marwin Segler (1 shared paper)Philipp Seidl (2 shared papers)
- Journals
- Journal of Chemical Information and Modeling (2 papers)Drug Discovery Today Technologies (1 paper)European Journal of Anaesthesiology (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- AustriaUnited StatesGermany
In The Last Decade
Philipp Renz
7 papers receiving 157 citations
Peers
Comparison fields: 5 of 41
- Computational Theory and Mathematics 106
- Anesthesiology and Pain Medicine 17
- Materials Chemistry 97
- Critical Care and Intensive Care Medicine 8
- Molecular Biology 80
Countries citing papers authored by Philipp Renz
This map shows the geographic impact of Philipp Renz'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 Renz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Renz more than expected).
Fields of papers citing papers by Philipp Renz
This network shows the impact of papers produced by Philipp Renz. 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 Renz. The network helps show where Philipp Renz may publish in the future.
Co-authors
The 19 scholars most cited alongside Philipp Renz, 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 | 2019 | 86 | |
| 2 | 2022 | 46 | |
| 3 | 2009 | 22 | |
| 4 | 2024 | 6 | |
| 5 | Fréchet ChemblNet Distance: A metric for generative models for molecules. | 2018 | 2 |
| 6 | Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. | 2021 | 1 |
| 7 | 2017 | 1 | |
| 8 | 2023 | 0 |
About Philipp Renz
Philipp Renz is a scholar working on Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Critical Care and Intensive Care Medicine and Control and Systems Engineering, having authored 8 papers that have together received 164 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (5 papers), Protein Structure and Dynamics (4 papers), Anesthesia and Sedative Agents (1 paper), Time Series Analysis and Forecasting (1 paper), Anesthesia and Neurotoxicity Research (1 paper), Power System Reliability and Maintenance (1 paper) and Reliability and Maintenance Optimization (1 paper). The work is most often cited by research in Computational Theory and Mathematics (106 citations), Anesthesiology and Pain Medicine (17 citations), Materials Chemistry (97 citations), Critical Care and Intensive Care Medicine (8 citations) and Molecular Biology (80 citations). Philipp Renz has collaborated with scholars based in Austria, United States and Germany. Frequent co-authors include Günter Klambauer, Sepp Hochreiter, Jörg K. Wegner, Dries Van Rompaey, Jonas Verhoeven, Natalia Dyubankova, Marwin Segler, Philipp Seidl, Peter H. Tonner and Thomas Ledowski. Their work appears in journals such as Journal of Chemical Information and Modeling, Drug Discovery Today Technologies, European Journal of Anaesthesiology and arXiv (Cornell University).
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.