Patrick Rubin‐Delanchy

24 papers receiving 436 citations

Peers

Patrick Rubin‐Delanchy
Comparison fields: 5 of 103
  • Structural Biology 59
  • Biophysics 147
  • Signal Processing 54
  • Statistics and Probability 40
  • Statistical and Nonlinear Physics 54
Replace Nicholas A. Heard with:
Nicholas A. Heard United Kingdom
Edward A. K. Cohen United States
Vasileios Maroulas United States
Adam M. Johansen United Kingdom
Grzegorz Sikora Poland
Keegan Hines United States
Hagai Kirshner Switzerland
Yanan Cai China
Stephan Huckemann Germany
Patrick Rubin‐Delanchy relative to Nicholas A. Heard United Kingdom Nicholas A. Heard's profile →
Citations per field
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Citations per year

Countries citing papers authored by Patrick Rubin‐Delanchy

Since Specialization
Citations

This map shows the geographic impact of Patrick Rubin‐Delanchy'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 Rubin‐Delanchy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Rubin‐Delanchy more than expected).

Fields of papers citing papers by Patrick Rubin‐Delanchy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick Rubin‐Delanchy. 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 Rubin‐Delanchy. The network helps show where Patrick Rubin‐Delanchy may publish in the future.

Co-authors

The 25 scholars most cited alongside Patrick Rubin‐Delanchy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Patrick Rubin‐Delanchy Line = papers co-authored together Patrick Rubin‐Delanchy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201592
2 201792
3 200843
4 201638
5 202236
6 201721
7 202221
8 200815
9 201414
10 201813
11 201612
12 201810
13 200710
14 20189
15 20184
16 20214
17 20164
18 20233
19 20142
20 20142

About Patrick Rubin‐Delanchy

Patrick Rubin‐Delanchy is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Biophysics, Computer Networks and Communications and Statistics and Probability, having authored 24 papers that have together received 450 indexed citations. Recurring topics across this work include Advanced Fluorescence Microscopy Techniques (7 papers), Complex Network Analysis Techniques (7 papers), Cell Image Analysis Techniques (5 papers), Network Security and Intrusion Detection (4 papers), Advanced Electron Microscopy Techniques and Applications (3 papers), Anomaly Detection Techniques and Applications (3 papers), Statistical Distribution Estimation and Applications (2 papers) and Graph theory and applications (2 papers). The work is most often cited by research in Structural Biology (59 citations), Biophysics (147 citations), Signal Processing (54 citations), Statistics and Probability (40 citations) and Statistical and Nonlinear Physics (54 citations). Patrick Rubin‐Delanchy has collaborated with scholars based in United Kingdom, United States and Portugal. Frequent co-authors include Nicholas A. Heard, Andrew T. Walden, Dylan M. Owen, David J. Williamson, Juliette Griffié, Garth L. Burn, Andrew P. Cope, Carey E. Priebe, Minh Tang and Joshua Cape. Their work appears in journals such as IEEE Transactions on Signal Processing, Nature Methods, Journal of the American Statistical Association, Nature Communications and Journal of the Royal Statistical Society Series B (Statistical Methodology).

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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