Jonathan Passerat-Palmbach

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 46

Top Venues

Blaise Pascal University, Clermont-Ferrand, France (PHD)

Education History

Blaise Pascal University, Clermont-Ferrand, France

PHD

Publications

Bianca-Mihaela Ganescu, Jonathan Passerat-Palmbach
Trust the Process: Zero-Knowledge Machine Learning to Enhance Trust in Generative AI Interactions. CoRR (2024)
Xinyuan Sun, Davide Crapis, Matt Stephenson, Barnabé Monnot, Thomas Thiery, Jonathan Passerat-Palmbach
Cooperative AI via Decentralized Commitment Devices. CoRR (2023)
Vasilis Siomos, Jonathan Passerat-Palmbach
Contribution Evaluation in Federated Learning: Examining Current Approaches. CoRR (2023)
Vasilis Siomos, Sergio Naval Marimont, Jonathan Passerat-Palmbach, Giacomo Tarroni
ARIA: On the interaction between Architectures, Aggregation methods and Initializations in federated visual classification. CoRR (2023)
Dmitrii Usynin, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis
Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning. Proc. Priv. Enhancing Technol. 2022 (1) (2022)
Vasilis Siomos, Giacomo Tarroni, Jonathan Passerat-Palmbach
FeTS Challenge 2022 Task 1: Implementing FedMGDA + and a New Partitioning. BrainLes@MICCAI (2) (2022)
George-Liviu Pereteanu, Amir Alansary, Jonathan Passerat-Palmbach
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption. CoRR (2022)
Dmitrii Usynin, Alexander Ziller, Marcus R. Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, Jonathan Passerat-Palmbach
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning. Nat. Mach. Intell. 3 (9) (2021)
Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis
Distributed Machine Learning and the Semblance of Trust. CoRR (2021)
Stefán Páll Sturluson, Samuel Trew, Luis Muñoz-González, Matei Grama, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary
FedRAD: Federated Robust Adaptive Distillation. CoRR (2021)
Ashly Lau, Jonathan Passerat-Palmbach
Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques. CoRR (2021)
Georgios Kaissis, Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Lima, Jason Mancuso, Friederike Jungmann, Marc-Matthias Steinborn, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren
End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nat. Mach. Intell. 3 (6) (2021)
Matei Grama, Maria Musat, Luis Muñoz-González, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare. CoRR (2020)
Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Da Lima Costa Junior, Jason Mancuso, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren, Georgios Kaissis
Privacy-preserving medical image analysis. CoRR (2020)
Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification. CoRR (2020)
Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification. PPMLP@CCS (2020)
Sean P. Fitzgibbon, Samuel J. Harrison, Mark Jenkinson, Luke Baxter, Emma C. Robinson, Matteo Bastiani, Jelena Bozek, Vyacheslav Karolis, Lucilio Cordero-Grande, Anthony N. Price, Emer J. Hughes, Antonios Makropoulos, Jonathan Passerat-Palmbach, Andreas Schuh, Jianliang Gao, Seyedeh-Rezvan Farahibozorg, Jonathan O'Muircheartaigh, Judit Ciarrusta, Jesper Andersson
The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants. NeuroImage 223 (2020)
Harry Cai, Daniel Rueckert, Jonathan Passerat-Palmbach
2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments. CoRR (2020)
Jonathan Passerat-Palmbach, Tyler Farnan, Mike McCoy, Justin D. Harris, Sean T. Manion, Heather Leigh Flannery, Bill Gleim
Blockchain-orchestrated machine learning for privacy preserving federated learning in electronic health data. Blockchain (2020)
Jonathan Passerat-Palmbach, Tyler Farnan, Robert Miller, Marielle S. Gross, Heather Leigh Flannery, Bill Gleim
A blockchain-orchestrated Federated Learning architecture for healthcare consortia. CoRR (2019)
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
Learning-Based Quality Control for Cardiac MR Images. IEEE Trans. Medical Imaging 38 (5) (2019)
Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Ben Glocker, Paul M. Matthews, Daniel Rueckert
Learning-Based Quality Control for Cardiac MR Images. CoRR (2018)
Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. CoRR (2018)
Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. MICCAI (1) (2018)
Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert
Multi-Atlas Segmentation Using Partially Annotated Data: Methods and Annotation Strategies. IEEE Trans. Pattern Anal. Mach. Intell. 40 (7) (2018)
Théo Ryffel, Andrew Trask, Morten Dahl, Bobby Wagner, Jason Mancuso, Daniel Rueckert, Jonathan Passerat-Palmbach
A generic framework for privacy preserving deep learning. CoRR (2018)
Antonios Makropoulos, Emma C. Robinson, Andreas Schuh, Robert Wright, Sean P. Fitzgibbon, Jelena Bozek, Serena J. Counsell, Johannes Steinweg, Katy Vecchiato, Jonathan Passerat-Palmbach, Gregor Lenz, Filippo Mortari, Tencho Tenev, Eugene P. Duff, Matteo Bastiani, Lucilio Cordero-Grande, Emer J. Hughes, Nora Tusor, Daniel Rueckert
The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction. NeuroImage 173 (2018)
Giacomo Tarroni, Ozan Oktay, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Jonathan Passerat-Palmbach, Ben Glocker, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert
Learning-Based Heart Coverage Estimation for Short-Axis Cine Cardiac MR Images. FIMH (2017)
Jonathan Passerat-Palmbach, Romain Reuillon, Mathieu Leclaire, Antonios Makropoulos, Emma C. Robinson, Sarah Parisot, Daniel Rueckert
Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System. Frontiers Neuroinformatics 11 (2017)
Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Mellisa Damodaram, Mary A. Rutherford, Joseph V. Hajnal, Bernhard Kainz, Daniel Rueckert
DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks. IEEE Trans. Medical Imaging 36 (2) (2017)
Martin Rajchl, Lisa M. Koch, Christian Ledig, Jonathan Passerat-Palmbach, Kazunari Misawa, Kensaku Mori, Daniel Rueckert
Employing Weak Annotations for Medical Image Analysis Problems. CoRR (2017)
Sarah Parisot, Jonathan Passerat-Palmbach, Markus D. Schirmer, Boris Gutman
Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016. CoRR (2016)
Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Bernhard Kainz, Daniel Rueckert
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks. CoRR (2016)
Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert
Group-wise parcellation of the cortex through multi-scale spectral clustering. NeuroImage 136 (2016)
Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert
Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies. CoRR (2016)
Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach, Daniel Rueckert
Comparison of Brain Networks with Unknown Correspondences. CoRR (2016)
Martin Rajchl, Matthew C. H. Lee, Franklin Schrans, Alice Davidson, Jonathan Passerat-Palmbach, Giacomo Tarroni, Amir Alansary, Ozan Oktay, Bernhard Kainz, Daniel Rueckert
Learning under Distributed Weak Supervision. CoRR (2016)
Romain Reuillon, Mathieu Leclaire, Jonathan Passerat-Palmbach
Model exploration using OpenMOLE a workflow engine for large scale distributed design of experiments and parameter tuning. HPCS (2015)
Jonathan Passerat-Palmbach, Claude Mazel, David R. C. Hill
TaskLocalRandom: a statistically sound substitute to pseudorandom number generation in parallel java tasks frameworks. Concurr. Comput. Pract. Exp. 27 (13) (2015)
Romain Reuillon, Mathieu Leclaire, Jonathan Passerat-Palmbach
Model Exploration Using OpenMOLE - a workflow engine for large scale distributed design of experiments and parameter tuning. CoRR (2015)
Sarah Parisot, Martin Rajchl, Jonathan Passerat-Palmbach, Daniel Rueckert
A Continuous Flow-Maximisation Approach to Connectivity-Driven Cortical Parcellation. MICCAI (3) (2015)
Lisa M. Koch, Martin Rajchl, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert
Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data. IPMI (2015)
Jonathan Passerat-Palmbach, Claude Mazel, Antoine Mahul, David R. C. Hill
Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors. CoRR (2015)
Jonathan Passerat-Palmbach, Jonathan Caux, Pierre Schweitzer, Pridi Siregar, Claude Mazel, David R. C. Hill
Harnessing aspect-oriented programming on GPU: application to warp-level parallelism. Int. J. Comput. Aided Eng. Technol. 7 (2) (2015)
Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert
Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex. IPMI (2015)
Jonathan Passerat-Palmbach, Jonathan Caux, Pridi Siregar, Claude Mazel, David R. C. Hill
Warp-Level Parallelism: Enabling Multiple Replications In Parallel on GPU. CoRR (2015)
Jonathan Passerat-Palmbach, David R. C. Hill
How to Correctly Deal With Pseudorandom Numbers in Manycore Environments - Application to GPU programming with Shoverand. CoRR (2014)
David R. C. Hill, Claude Mazel, Jonathan Passerat-Palmbach, Mamadou Kaba Traoré
Distribution of random streams for simulation practitioners. Concurr. Comput. Pract. Exp. 25 (10) (2013)
Jonathan Passerat-Palmbach, Jonathan Caux, Yannick Le Pennec, Romain Reuillon, Ivan Junier, François Képès, David R. C. Hill
Parallel stepwise stochastic simulation: harnessing GPUs to explore possible futures states of a chromosome folding model thanks to the possible futures algorithm (PFA). SIGSIM-PADS (2013)
Jonathan Passerat-Palmbach, Romain Reuillon, Claude Mazel, David R. C. Hill
Prototyping parallel simulations on manycore architectures using Scala: A case study. HPCS (2013)
Romain Reuillon, Mamadou K. Traoré, Jonathan Passerat-Palmbach, David R. C. Hill
Parallel stochastic simulations with rigorous distribution of pseudo-random numbers with DistMe: Application to life science simulations. Concurr. Comput. Pract. Exp. 24 (7) (2012)
Hesham H. Ali, Laura Ricci, Italo Epicoco, Manuel Ujaldon, Jonathan Passerat-Palmbach, David R. C. Hill, Manuel Villén-Altamirano
HPCS 2012 tutorials: Tutorial I: High performance computing in biomedical informatics. HPCS (2012)
Jonathan Passerat-Palmbach, Claude Mazel, David R. C. Hill
Pseudo-random streams for distributed and parallel stochastic simulations on GP-GPU. J. Simulation 6 (3) (2012)
Jonathan Passerat-Palmbach, David R. C. Hill
How to correctly deal with pseudorandom numbers in manycore environments: Application to GPU programming with Shoverand. HPCS (2012)
Jonathan Passerat-Palmbach, Claude Mazel, David R. C. Hill
ThreadLocalMRG32k3a: A statistically sound substitute to pseudorandom number generation in parallel Java applications. HPCS (2012)
Jonathan Passerat-Palmbach, Claude Mazel, David R. C. Hill
Pseudo-Random Number Generation on GP-GPU. PADS (2011)
Jonathan Passerat-Palmbach, Claude Mazel, Bruno Bachelet, David R. C. Hill
ShoveRand: A model-driven framework to easily generate random numbers on GP-GPU. HPCS (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jonathan Passerat-Palmbach