Patrick Kidger
Impact in
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- Model Reduction and Neural Networks
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- Neural Networks and Applications
Papers in
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- Neural Networks and Applications 2
- Algorithms and Data Compression 1
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- Model Reduction and Neural Networks 2
- Co-authors
- Terry Lyons (3 shared papers)James Morrill (1 shared paper)James Foster (1 shared paper)Imanol Pérez Arribas (1 shared paper)Toshiyuki Bandai (2 shared papers)Carl I. Steefel (2 shared papers)Xingyuan Chen (2 shared papers)Teamrat A. Ghezzehei (1 shared paper)
- Journals
- Water Resources Research (2 papers)Oxford University Research Archive (ORA) (University of Oxford) (2 papers)Neural Information Processing Systems (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Patrick Kidger
5 papers receiving 29 citations
Peers
Comparison fields: 5 of 30
- Statistical and Nonlinear Physics 12
- Artificial Intelligence 15
- Statistics, Probability and Uncertainty 2
- Hardware and Architecture 2
- Environmental Engineering 4
Countries citing papers authored by Patrick Kidger
This map shows the geographic impact of Patrick Kidger'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 Kidger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Kidger more than expected).
Fields of papers citing papers by Patrick Kidger
This network shows the impact of papers produced by Patrick Kidger. 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 Kidger. The network helps show where Patrick Kidger may publish in the future.
Co-authors
The 13 scholars most cited alongside Patrick Kidger, 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 | Neural Controlled Differential Equations for Irregular Time Series | 2020 | 14 |
| 2 | Deep Signature Transforms | 2019 | 8 |
| 3 | 2024 | 6 | |
| 4 | 2025 | 2 | |
| 5 | Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU | 2021 | 1 |
About Patrick Kidger
Patrick Kidger is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Environmental Engineering, Civil and Structural Engineering and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 31 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (2 papers), Neural Networks and Applications (2 papers), Hydrological Forecasting Using AI (1 paper), Hydrology and Watershed Management Studies (1 paper), Plant Water Relations and Carbon Dynamics (1 paper), Algorithms and Data Compression (1 paper), Digital Media Forensic Detection (1 paper) and Groundwater flow and contamination studies (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (12 citations), Artificial Intelligence (15 citations), Statistics, Probability and Uncertainty (2 citations), Hardware and Architecture (2 citations) and Environmental Engineering (4 citations). Patrick Kidger has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Terry Lyons, James Morrill, James Foster, Imanol Pérez Arribas, Toshiyuki Bandai, Carl I. Steefel, Xingyuan Chen, Teamrat A. Ghezzehei, Peishi Jiang and Heping Liu. Their work appears in journals such as Water Resources Research, Oxford University Research Archive (ORA) (University of Oxford) and Neural Information Processing Systems.
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.