Conor Durkan
Impact in
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- Gamma-ray bursts and supernovae
- Cosmology and Gravitation Theories
- Pulsars and Gravitational Waves Research
- Galaxies: Formation, Evolution, Phenomena
- Stellar, planetary, and galactic studies
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- Particle physics theoretical and experimental studies
Papers in
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- Advanced Image Processing Techniques 1
- Generative Adversarial Networks and Image Synthesis 1
- Advanced Vision and Imaging 1
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- Model Reduction and Neural Networks 1
- Journals
- Zenodo (CERN European Organization for Nuclear Research) (1 paper)International Conference on Machine Learning (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
Conor Durkan
3 papers receiving 43 citations
Peers
Comparison fields: 5 of 29
- Astronomy and Astrophysics 17
- Nuclear and High Energy Physics 13
- Instrumentation 2
- Computer Graphics and Computer-Aided Design 2
- Statistical and Nonlinear Physics 5
Countries citing papers authored by Conor Durkan
This map shows the geographic impact of Conor Durkan'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 Conor Durkan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Conor Durkan more than expected).
Fields of papers citing papers by Conor Durkan
This network shows the impact of papers produced by Conor Durkan. 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 Conor Durkan. The network helps show where Conor Durkan may publish in the future.
Co-authors
The 2 scholars most cited alongside Conor Durkan, 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 | 2020 | 37 | |
| 2 | 2020 | 7 | |
| 3 | Cubic-Spline Flows | 2019 | 1 |
About Conor Durkan
Conor Durkan is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Artificial Intelligence, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 45 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (1 paper), Advanced Image Processing Techniques (1 paper), Model Reduction and Neural Networks (1 paper), Machine Learning and Algorithms (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Astronomy and Astrophysics (17 citations), Nuclear and High Energy Physics (13 citations), Instrumentation (2 citations), Computer Graphics and Computer-Aided Design (2 citations) and Statistical and Nonlinear Physics (5 citations). Conor Durkan has collaborated with scholars based in United Kingdom. Frequent co-authors include George Papamakarios and Iain Murray. Their work appears in journals such as Zenodo (CERN European Organization for Nuclear Research), International Conference on Machine Learning 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.