Jonathan Passerat‐Palmbach

3.2k total citations · 1 hit paper
18 papers, 773 citations indexed

About

Jonathan Passerat‐Palmbach is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Jonathan Passerat‐Palmbach has authored 18 papers receiving a total of 773 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Cognitive Neuroscience. Recurrent topics in Jonathan Passerat‐Palmbach's work include Functional Brain Connectivity Studies (5 papers), Privacy-Preserving Technologies in Data (4 papers) and Algorithms and Data Compression (4 papers). Jonathan Passerat‐Palmbach is often cited by papers focused on Functional Brain Connectivity Studies (5 papers), Privacy-Preserving Technologies in Data (4 papers) and Algorithms and Data Compression (4 papers). Jonathan Passerat‐Palmbach collaborates with scholars based in United Kingdom, France and United States. Jonathan Passerat‐Palmbach's co-authors include Daniel Rueckert, Wenjia Bai, Ozan Oktay, Martin Rajchl, Joseph V. Hajnal, Dmitrii Usynin, Georgios Kaissis, Bernhard Kainz, Mellisa Damodaram and Konstantinos Kamnitsas and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.

In The Last Decade

Jonathan Passerat‐Palmbach

18 papers receiving 763 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

End-to-end privacy preserving deep learning on multi-institutional medical imaging

2021 255 citations Georgios Kaissis, Alexander Ziller et al. Nature Machine Intelligence profile →

Peers

Countries citing papers authored by Jonathan Passerat‐Palmbach

Since Specialization

Citations

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

Fields of papers citing papers by Jonathan Passerat‐Palmbach

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Passerat‐Palmbach. 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 Jonathan Passerat‐Palmbach. The network helps show where Jonathan Passerat‐Palmbach may publish in the future.

Co-authorship network of co-authors of Jonathan Passerat‐Palmbach

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

All Works

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18 of 18 papers shown

#	Work	Indexed citations
1	End-to-end privacy preserving deep learning on multi-institutional medical imaging breakdown → 2021 ·Nature Machine Intelligence ·Georgios Kaissis, Alexander Ziller, Jonathan Passerat‐Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, (unknown), Jason Mancuso, Friederike Jungmann, M. Steinborn, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren	255
2	Adversarial interference and its mitigations in privacy-preserving collaborative machine learning 2021 ·Nature Machine Intelligence ·Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat‐Palmbach	32
3	Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning 2021 ·SHILAP Revista de lepidopterología ·Dmitrii Usynin, Daniel Rueckert, Jonathan Passerat‐Palmbach, Georgios Kaissis	7
4	Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain 2020 ·PLoS Biology ·Gareth Ball, Jakob Seidlitz, Jonathan O’Muircheartaigh, Ralica Dimitrova, Daphna Fenchel, Antonios Makropoulos, Daan Christiaens, Andreas Schuh, Jonathan Passerat‐Palmbach, Jana Hutter, Lucilio Cordero‐Grande, Emer Hughes, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert, Emma C. Robinson, A. David Edwards	34
5	Blockchain-orchestrated machine learning for privacy preserving federated learning in electronic health data 2020 ·Jonathan Passerat‐Palmbach, (unknown), Mike McCoy, (unknown), (unknown), (unknown), (unknown)	55
6	Fostering the use of methods for geosimulation models sensitivity analysis and validation 2019 ·Agritrop (Cirad) ·Romain Reuillon, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Jonathan Passerat‐Palmbach, (unknown), Julien Perret, (unknown)	1
7	Learning-Based Quality Control for Cardiac MR Images 2018 ·IEEE Transactions on Medical Imaging ·Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat‐Palmbach, Antonio de Marvao, Declan P. O’Regan, Stuart A. Cook, Ben Glocker, Paul M. Matthews, Daniel Rueckert	37
8	Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System 2017 ·Frontiers in Neuroinformatics ·Jonathan Passerat‐Palmbach, Romain Reuillon, (unknown), Antonios Makropoulos, Emma C. Robinson, Sarah Parisot, Daniel Rueckert	2
9	Multi-Atlas Segmentation Using Partially Annotated Data: Methods and Annotation Strategies 2017 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat‐Palmbach, Paul Aljabar, Daniel Rueckert	9
10	Group-wise parcellation of the cortex through multi-scale spectral clustering 2016 ·NeuroImage ·Sarah Parisot, Salim Arslan, Jonathan Passerat‐Palmbach, William M. Wells, Daniel Rueckert	29
11	DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks 2016 ·IEEE Transactions on Medical Imaging ·Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat‐Palmbach, Wenjia Bai, Mellisa Damodaram, Mary Rutherford, Joseph V. Hajnal, Bernhard Kainz, Daniel Rueckert	257
12	Comparison of Brain Networks with Unknown Correspondences 2016 ·arXiv (Cornell University) ·Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat‐Palmbach, Daniel Rueckert	1
13	Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data 2015 ·Lecture notes in computer science ·Lisa M. Koch, Martin Rajchl, Tong Tong, Jonathan Passerat‐Palmbach, Paul Aljabar, Daniel Rueckert	9
14	Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex 2015 ·Lecture notes in computer science ·Sarah Parisot, Salim Arslan, Jonathan Passerat‐Palmbach, William M. Wells, Daniel Rueckert	14
15	TaskLocalRandom: a statistically sound substitute to pseudorandom number generation in parallel java tasks frameworks 2014 ·Concurrency and Computation Practice and Experience ·Jonathan Passerat‐Palmbach, (unknown), David R.C. Hill	2
16	Pseudo-random streams for distributed and parallel stochastic simulations on GP-GPU 2012 ·Journal of Simulation ·Jonathan Passerat‐Palmbach, (unknown), David R.C. Hill	5
17	Distribution of random streams for simulation practitioners 2012 ·Concurrency and Computation Practice and Experience ·David R.C. Hill, (unknown), Jonathan Passerat‐Palmbach, Mamadou Kaba Traoré	16
18	Parallel stochastic simulations with rigorous distribution of pseudo‐random numbers with DistMe: Application to life science simulations 2011 ·Concurrency and Computation Practice and Experience ·Romain Reuillon, Mamadou Kaba Traoré, Jonathan Passerat‐Palmbach, David R.C. Hill	8

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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