Robin Winter
Impact in
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- Computational Drug Discovery Methods
- Artificial Intelligence top 2%
- Neural Networks and Applications
- Fuzzy Logic and Control Systems
- Neural Networks and Reservoir Computing
Papers in
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- Computational Drug Discovery Methods 6
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- Machine Learning in Bioinformatics 2
- Cancer therapeutics and mechanisms 1
- Co-authors
- Bernard Widrow (3 shared papers)Djork-Arné Clevert (5 shared papers)Frank Noé (5 shared papers)Floriane Montanari (3 shared papers)Rohan A. Baxter (1 shared paper)M. Stevenson (1 shared paper)Andreas Steffen (2 shared papers)Hans Briem (1 shared paper)
- Journals
- Chemical Science (4 papers)International Journal of Molecular Sciences (1 paper)Nature Communications (1 paper)Bioinformatics (1 paper)Computer (1 paper)
- Partner nations
- GermanyUnited States
In The Last Decade
Robin Winter
9 papers receiving 1.2k citations
Robin Winter's Hit Papers
Peers
Comparison fields: 5 of 118
- Computational Theory and Mathematics 496
- Artificial Intelligence 575
- Signal Processing 136
- Computer Vision and Pattern Recognition 193
- Materials Chemistry 358
Countries citing papers authored by Robin Winter
This map shows the geographic impact of Robin Winter'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 Robin Winter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robin Winter more than expected).
Fields of papers citing papers by Robin Winter
This network shows the impact of papers produced by Robin Winter. 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 Robin Winter. The network helps show where Robin Winter may publish in the future.
Co-authors
The 19 scholars most cited alongside Robin Winter, 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 | Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations Hit paper breakdown → | 2018 | 326 |
| 2 | 1988 | 307 | |
| 3 | 1988 | 256 | |
| 4 | 1990 | 158 | |
| 5 | 2019 | 156 | |
| 6 | 2020 | 40 | |
| 7 | 2021 | 38 | |
| 8 | 2020 | 9 | |
| 9 | 2021 | 8 | |
| 10 | 2025 | 0 |
About Robin Winter
Robin Winter is a scholar working on Computational Theory and Mathematics, Molecular Biology, Artificial Intelligence, Materials Chemistry and Spectroscopy, having authored 10 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Neural Networks and Applications (3 papers), Machine Learning in Materials Science (3 papers), Machine Learning in Bioinformatics (2 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers), Cholinesterase and Neurodegenerative Diseases (1 paper), SARS-CoV-2 and COVID-19 Research (1 paper) and Cancer therapeutics and mechanisms (1 paper). The work is most often cited by research in Computational Theory and Mathematics (496 citations), Artificial Intelligence (575 citations), Signal Processing (136 citations), Computer Vision and Pattern Recognition (193 citations) and Materials Chemistry (358 citations). Robin Winter has collaborated with scholars based in Germany and United States. Frequent co-authors include Bernard Widrow, Djork-Arné Clevert, Frank Noé, Floriane Montanari, Rohan A. Baxter, M. Stevenson, Andreas Steffen, Hans Briem, Tuan Le and Joren Sebastian Retel. Their work appears in journals such as Chemical Science, International Journal of Molecular Sciences, Nature Communications, Bioinformatics and Computer.
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.