Conor Durkan

407 total citations
3 papers, 45 citations indexed

About

Conor Durkan is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Conor Durkan has authored 3 papers receiving a total of 45 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Computer Vision and Pattern Recognition, 1 paper in Statistical and Nonlinear Physics and 1 paper in Artificial Intelligence. Recurrent topics in Conor Durkan's work include Advanced Vision and Imaging (1 paper), Machine Learning and Algorithms (1 paper) and Model Reduction and Neural Networks (1 paper). Conor Durkan is often cited by papers focused on Advanced Vision and Imaging (1 paper), Machine Learning and Algorithms (1 paper) and Model Reduction and Neural Networks (1 paper). Conor Durkan collaborates with scholars based in United Kingdom. Conor Durkan's co-authors include George Papamakarios and Iain Murray and has published in prestigious journals such as arXiv (Cornell University), International Conference on Machine Learning and Zenodo (CERN European Organization for Nuclear Research).

In The Last Decade

Conor Durkan

3 papers receiving 43 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Conor Durkan United Kingdom	2	17	13	12	6	5	3	45
J. Krupa United States	5	15 0.9×	6 0.5×	11 0.9×	7 1.2×	5 1.0×	5	35
M. Hushchyn Russia	5	9 0.5×	14 1.1×	12 1.0×	5 0.8×	2 0.4×	15	50
Marco Bonici Italy	5	52 3.1×	17 1.3×	11 0.9×	4 0.7×	7 1.4×	12	72
F Tarsitano Switzerland	4	26 1.5×	12 0.9×	5 0.4×	8 1.3×	2 0.4×	4	39
D. Forero-Sánchez Switzerland	4	39 2.3×	7 0.5×	5 0.4×	3 0.5×	6 1.2×	7	42
Kushal Tirumala Israel	3	27 1.6×	7 0.5×	12 1.0×	4 0.7×		3	46
K. Borras Germany	5	6 0.4×	17 1.3×	25 2.1×	3 0.5×	2 0.4×	12	43
D. Zürcher Switzerland	3	54 3.2×	15 1.2×	4 0.3×	4 0.7×	3 0.6×	3	58
S. Donzelli Italy	3	35 2.1×	10 0.8×	7 0.6×	1 0.2×	4 0.8×	4	45
E. Tolley Switzerland	4	22 1.3×	11 0.8×	6 0.5×	1 0.2×	3 0.6×	10	31

Countries citing papers authored by Conor Durkan

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Conor Durkan

This figure shows the co-authorship network connecting the top 25 collaborators of Conor Durkan. A scholar is included among the top collaborators of Conor Durkan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Conor Durkan. Conor Durkan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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3 of 3 papers shown

1.

Durkan, Conor, Iain Murray, & George Papamakarios. (2020). On Contrastive Learning for Likelihood-free Inference. arXiv (Cornell University). 1. 2771–2781. 7 indexed citations

2.

Durkan, Conor, et al.. (2020). nflows: normalizing flows in PyTorch. Zenodo (CERN European Organization for Nuclear Research). 37 indexed citations

3.

Durkan, Conor, et al.. (2019). Cubic-Spline Flows. International Conference on Machine Learning. 1 indexed citations

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.

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