Claire Donnat

1.9k total citations
11 papers, 120 citations indexed

About

Claire Donnat is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, Claire Donnat has authored 11 papers receiving a total of 120 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Statistical and Nonlinear Physics, 3 papers in Artificial Intelligence and 2 papers in Infectious Diseases. Recurrent topics in Claire Donnat's work include Complex Network Analysis Techniques (3 papers), Bioinformatics and Genomic Networks (2 papers) and Advanced Graph Neural Networks (2 papers). Claire Donnat is often cited by papers focused on Complex Network Analysis Techniques (3 papers), Bioinformatics and Genomic Networks (2 papers) and Advanced Graph Neural Networks (2 papers). Claire Donnat collaborates with scholars based in United States, United Kingdom and Estonia. Claire Donnat's co-authors include Susan Holmes, Frédéric Poitevin, Ellen D. Zhong, Nina Miolane, Jure Leskovec, Marinka Žitnik, David Hallac, Hannah Wang, Joseph E. Tonna and Renè Vidal and has published in prestigious journals such as Journal of Structural Biology, Statistical Science and Artificial Organs.

In The Last Decade

Claire Donnat

11 papers receiving 118 citations

Peers

Claire Donnat

SNP

AI

MB

EE

SB

Nasim Rahaman Germany

Will Grathwohl Canada

Georg Hahn United States

Adam Hackett Ireland

Yannik Schälte Germany

Huber Nieto–Chaupis Peru

Atte Aalto Luxembourg

Malaikannan Sankarasubbu India

Andrey Pilipenko Ukraine

Nasim Rahaman Germany

Claire Donnat

25 ×0.5

SNP

35 ×1.1

AI

7 ×0.3

MB

4 ×0.3

EE

4 ×0.4

SB

Citations per year, relative to Claire Donnat Claire Donnat (= 1×) peers Nasim Rahaman

Countries citing papers authored by Claire Donnat

Since Specialization

Citations

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

Fields of papers citing papers by Claire Donnat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Claire Donnat. 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 Claire Donnat. The network helps show where Claire Donnat may publish in the future.

Co-authorship network of co-authors of Claire Donnat

This figure shows the co-authorship network connecting the top 25 collaborators of Claire Donnat. A scholar is included among the top collaborators of Claire Donnat 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 Claire Donnat. Claire Donnat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Ferreira, Rodrigo José Pires, Rui Ding, Fengxue Zhang, et al.. (2025). Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks. Molecular Systems Design & Engineering. 10(5). 345–356. 1 indexed citations

2.

Donnat, Claire, et al.. (2023). A Simplified Framework for Contrastive Learning for Node Representations. 573–577. 1 indexed citations

3.

Donnat, Claire, et al.. (2022). Deep generative modeling for volume reconstruction in cryo-electron microscopy. Journal of Structural Biology. 214(4). 107920–107920. 14 indexed citations

4.

Wang, Hannah, et al.. (2022). Statistical Modeling for Practical Pooled Testing During the COVID-19 Pandemic. Statistical Science. 37(2). 9 indexed citations

5.

Owyang, Clark G., Claire Donnat, Daniel Brodie, et al.. (2022). Similarities in extracorporeal membrane oxygenation management across intensive care unit types in the United States: An analysis of the Extracorporeal Life Support Organization Registry. Artificial Organs. 46(7). 1369–1381. 6 indexed citations

6.

Donnat, Claire, David Liu, Filippos T Filippidis, et al.. (2021). Predicting COVID-19 Transmission to Inform the Management of Mass Events: Model-Based Approach. JMIR Public Health and Surveillance. 7(12). e30648–e30648. 6 indexed citations

7.

Miolane, Nina, Benjamin Hou, Stefan Heyder, et al.. (2020). Introduction to Geometric Learning in Python with Geomstats. Proceedings of the Python in Science Conferences. 48–57. 3 indexed citations

8.

Donnat, Claire, Marinka Žitnik, David Hallac, & Jure Leskovec. (2018). Spectral Graph Wavelets for Structural Role Similarity in Networks. arXiv (Cornell University). 9 indexed citations

9.

Donnat, Claire & Susan Holmes. (2018). Tracking Network Dynamics: a review of distances and similarity metrics.. arXiv (Cornell University). 8 indexed citations

10.

Donnat, Claire & Susan Holmes. (2018). Tracking network dynamics: A survey using graph distances. The Annals of Applied Statistics. 12(2). 61 indexed citations

11.

You, Chong, Claire Donnat, Daniel P. Robinson, & Renè Vidal. (2016). A divide-and-conquer framework for large-scale subspace clustering. 17. 1014–1018. 2 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.

Explore authors with similar magnitude of impact