Patrick Riley
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Materials Chemistry top 5%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
Papers in
-
- Computational Drug Discovery Methods 9
- Advanced Multi-Objective Optimization Algorithms 2
-
- Machine Learning in Materials Science 11
- Co-authors
- Steven M. Kearnes (6 shared papers)Kevin McCloskey (2 shared papers)Marc Berndl (2 shared papers)Vijay S. Pande (1 shared paper)Justin Gilmer (2 shared papers)Samuel S. Schoenholz (2 shared papers)George E. Dahl (2 shared papers)Oriol Vinyals (2 shared papers)
- Journals
- Science Advances (3 papers)Journal of Medicinal Chemistry (3 papers)Journal of Affective Disorders (3 papers)Journal of Computer-Aided Molecular Design (2 papers)Journal of Chemical Information and Modeling (2 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Patrick Riley
24 papers receiving 3.1k citations
Patrick Riley's Hit Papers
Peers
Comparison fields: 5 of 162
- Computational Theory and Mathematics 1.3k
- Materials Chemistry 1.5k
- Molecular Biology 975
- Artificial Intelligence 414
- Physical and Theoretical Chemistry 101
Countries citing papers authored by Patrick Riley
This map shows the geographic impact of Patrick Riley'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 Patrick Riley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Riley more than expected).
Fields of papers citing papers by Patrick Riley
This network shows the impact of papers produced by Patrick Riley. 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 Patrick Riley. The network helps show where Patrick Riley may publish in the future.
Co-authors
The 25 scholars most cited alongside Patrick Riley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Molecular graph convolutions: moving beyond fingerprints Hit paper breakdown → | 2016 | 1166 |
| 2 | Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error Hit paper breakdown → | 2017 | 492 |
| 3 | 2020 | 238 | |
| 4 | Deep diversification of an AAV capsid protein by machine learning Hit paper breakdown → | 2021 | 204 |
| 5 | 1990 | 165 | |
| 6 | 2021 | 133 | |
| 7 | 2019 | 114 | |
| 8 | 2020 | 112 | |
| 9 | 2020 | 85 | |
| 10 | 2020 | 79 | |
| 11 | 2022 | 73 | |
| 12 | 2021 | 57 | |
| 13 | 2022 | 33 | |
| 14 | 2021 | 31 | |
| 15 | 2024 | 30 | |
| 16 | 2017 | 29 | |
| 17 | 1973 | 28 | |
| 18 | 1992 | 28 | |
| 19 | 2022 | 28 | |
| 20 | 2022 | 14 |
About Patrick Riley
Patrick Riley is a scholar working on Computational Theory and Mathematics, Materials Chemistry, Artificial Intelligence, Experimental and Cognitive Psychology and Molecular Biology, having authored 26 papers that have together received 3.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (11 papers), Computational Drug Discovery Methods (9 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Gaussian Processes and Bayesian Inference (2 papers), Advanced Graph Neural Networks (2 papers), Protein Structure and Dynamics (2 papers), Fault Detection and Control Systems (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Materials Chemistry (1.5k citations), Molecular Biology (975 citations), Artificial Intelligence (414 citations) and Physical and Theoretical Chemistry (101 citations). Patrick Riley has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Steven M. Kearnes, Kevin McCloskey, Marc Berndl, Vijay S. Pande, Justin Gilmer, Samuel S. Schoenholz, George E. Dahl, Oriol Vinyals, Peter J Tyrer and Siobhan M. Murphy. Their work appears in journals such as Science Advances, Journal of Medicinal Chemistry, Journal of Affective Disorders, Journal of Computer-Aided Molecular Design 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.