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Marco Lorenzi

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affiliation: Université Côte d'Azur, France

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Books and Theses

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2020
[b2]
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Marco Lorenzi:
Modelling pathological processes from heterogeneous and high-dimensional biomedical data. University of Nice Sophia Antipolis, France, 2020
2012
[b1]
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Marco Lorenzi:
Deformation-based morphometry of the brain for the development of surrogate markers in Alzheimer's disease. University of Nice Sophia Antipolis, France, 2012

Journal Articles

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2024
[j22]
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Riccardo Taiello, Melek Önen, Francesco Capano, Olivier Humbert, Marco Lorenzi:
Privacy preserving image registration. Medical Image Anal. 94: 103129 (2024)
2023
[j21]
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. J. Mach. Learn. Res. 24: 110:1-110:43 (2023)
[j20]
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Gerard Martí-Juan, Marco Lorenzi, Gemma Piella, Alzheimer's Disease Neuroimaging Initiative:
MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer's disease progression modelling. NeuroImage 268: 119892 (2023)
2022
[j19]
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Vien Ngoc Dang, Francesco Galati, Rosa Cortese, Giuseppe Di Giacomo, Viola Marconetto, Prateek Mathur, Karim Lekadir, Marco Lorenzi, Ferran Prados, Maria A. Zuluaga:
Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation. Medical Image Anal. 75: 102263 (2022)
[j18]
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Adrià Casamitjana, Marco Lorenzi, Sebastiano Ferraris, Loïc Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren, Juan Eugenio Iglesias:
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas. Medical Image Anal. 75: 102265 (2022)
[j17]
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Andres Diaz-Pinto, Nishant Ravikumar, Rahman Attar, Avan Suinesiaputra, Yitian Zhao, Eylem Levelt, Erica Dall' Armellina, Marco Lorenzi, Qingyu Chen, Tiarnan D. L. Keenan, Elvira Agrón, Emily Y. Chew, Zhiyong Lu, Chris P. Gale, Richard P. Gale, Sven Plein, Alejandro F. Frangi:
Predicting myocardial infarction through retinal scans and minimal personal information. Nat. Mach. Intell. 4(1): 55-61 (2022)
2021
[j16]
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Georgios Lazaridis, Marco Lorenzi, Sébastien Ourselin, David Garway-Heath:
Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks. Medical Image Anal. 68: 101906 (2021)
[j15]
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Jaume Banus, Marco Lorenzi, Oscar Camara, Maxime Sermesant:
Biophysics-based statistical learning: Application to heart and brain interactions. Medical Image Anal. 72: 102089 (2021)
[j14]
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Sara Garbarino, Marco Lorenzi, Alzheimer's Disease Neuroimaging Initiative:
Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain. NeuroImage 235: 117980 (2021)
2020
[j13]
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Clément Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi, Alzheimer's Disease Neuroimaging Initiative:
Monotonic Gaussian Process for spatio-temporal disease progression modeling in brain imaging data. NeuroImage 205 (2020)
2019
[j12]
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Claire Cury, Stanley Durrleman, David M. Cash, Marco Lorenzi, Jennifer M. Nicholas, Martina Bocchetta, John van Swieten, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Caroline Graff, Fabrizio Tagliavini, Giovanni B. Frisoni, Robert Laforce Jr., Elizabeth C. Finger, Alexandre de Mendonça, Jason D. Warren:
Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort. NeuroImage 188: 282-290 (2019)
[j11]
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Marco Lorenzi, Maurizio Filippone, Giovanni B. Frisoni, Daniel C. Alexander, Sébastien Ourselin:
Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease. NeuroImage 190: 56-68 (2019)
[j10]
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Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Sebastian J. Crutch, Daniel C. Alexander:
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. NeuroImage 192: 166-177 (2019)
[j9]
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Raphaël Sivera, Hervé Delingette, Marco Lorenzi, Xavier Pennec, Nicholas Ayache:
A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments. NeuroImage 198: 255-270 (2019)
2018
[j8]
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Sebastiano Ferraris, Johannes L. van der Merwe, Lennart Van Der Veeken, Ferran Prados, Juan Eugenio Iglesias, Andrew Melbourne, Marco Lorenzi, Marc Modat, Willy Gsell, Jan Deprest, Tom Vercauteren:
A magnetic resonance multi-atlas for the neonatal rabbit brain. NeuroImage 179: 187-198 (2018)
[j7]
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Marco Lorenzi, André Altmann, Boris Gutman, Selina Wray, Charles Arber, Derrek P. Hibar, Neda Jahanshad, Jonathan M. Schott, Daniel C. Alexander, Paul M. Thompson, Sébastien Ourselin:
Susceptibility of brain atrophy to TRIB3 in Alzheimer's disease, evidence from functional prioritization in imaging genetics. Proc. Natl. Acad. Sci. USA 115(12): 3162-3167 (2018)
2016
[j6]
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Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, Xavier Pennec:
A biophysical model of brain deformation to simulate and analyze longitudinal MRIs of patients with Alzheimer's disease. NeuroImage 134: 35-52 (2016)
2015
[j5]
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Marco Lorenzi, Nicholas Ayache, Xavier Pennec:
Regional flux analysis for discovering and quantifying anatomical changes: An application to the brain morphometry in Alzheimer's disease. NeuroImage 115: 224-234 (2015)
[j4]
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David M. Cash, Chris Frost, Leonardo O. Iheme, Devrim Ünay, Melek Kandemir, Jurgen Fripp, Olivier Salvado, Pierrick Bourgeat, Martin Reuter, Bruce Fischl, Marco Lorenzi, Giovanni B. Frisoni, Xavier Pennec, Ronald K. Pierson, Jeffrey L. Gunter, Matthew L. Senjem, Clifford R. Jack Jr., Nicolas Guizard, Vladimir S. Fonov, D. Louis Collins, Marc Modat, M. Jorge Cardoso, Kelvin K. Leung, Hongzhi Wang, Sandhitsu R. Das, Paul A. Yushkevich, Ian B. Malone, Nick C. Fox, Jonathan M. Schott, Sébastien Ourselin:
Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge. NeuroImage 123: 149-164 (2015)
2014
[j3]
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Marco Lorenzi, Xavier Pennec:
Efficient Parallel Transport of Deformations in Time Series of Images: From Schild's to Pole Ladder. J. Math. Imaging Vis. 50(1-2): 5-17 (2014)
2013
[j2]
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Marco Lorenzi, Xavier Pennec:
Geodesics, Parallel Transport & One-Parameter Subgroups for Diffeomorphic Image Registration. Int. J. Comput. Vis. 105(2): 111-127 (2013)
[j1]
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Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, Xavier Pennec:
LCC-Demons: A robust and accurate symmetric diffeomorphic registration algorithm. NeuroImage 81: 470-483 (2013)

Conference and Workshop Papers

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2024
[c40]
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Riccardo Taiello, Melek Önen, Clémentine Gritti, Marco Lorenzi:
Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Stragglers. ARES 2024: 13:1-13:12
[c39]
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Yann Fraboni, Martin Van Waerebeke, Kevin Scaman, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization. AISTATS 2024: 3457-3465
2023
[c38]
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Yann Fraboni, Lucia Innocenti, Michela Antonelli, Richard Vidal, Laetitia Kameni, Sébastien Ourselin, Marco Lorenzi:
Validation of Federated Unlearning on Collaborative Prostate Segmentation. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 322-333
2022
[c37]
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Federica Cruciani, André Altmann, Marco Lorenzi, Gloria Menegaz, Ilaria Boscolo Galazzo:
What PLS can still do for Imaging Genetics in Alzheimer's disease. BHI 2022: 1-4
[c36]
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
A General Theory for Client Sampling in Federated Learning. FL@IJCAI 2022: 46-58
[c35]
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Riccardo Taiello, Melek Önen, Olivier Humbert, Marco Lorenzi:
Privacy Preserving Image Registration. MICCAI (6) 2022: 130-140
[c34]
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Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux:
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS 2022
2021
[c33]
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Yann Fraboni, Richard Vidal, Marco Lorenzi:
Free-rider Attacks on Model Aggregation in Federated Learning. AISTATS 2021: 1846-1854
[c32]
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Heba Elshatoury, Federica Cruciani, Francesco Zumerle, Silvia Francesca Storti, André Altmann, Marco Lorenzi, Gholamreza Anbarjafari, Gloria Menegaz, Ilaria Boscolo Galazzo:
Disentangling the association between genetics and functional connectivity in Mild Cognitive Impairment. BHI 2021: 1-4
[c31]
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning. ICML 2021: 3407-3416
[c30]
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Irene Balelli, Santiago Silva, Marco Lorenzi:
A Probabilistic Framework for Modeling the Variability Across Federated Datasets. IPMI 2021: 701-714
[c29]
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Lorenza Brusini, Federica Cruciani, Ilaria Boscolo Galazzo, Marco Pitteri, Silvia Francesca Storti, Massimiliano Calabrese, Marco Lorenzi, Gloria Menegaz:
Multivariate Data Analysis Suggests The Link Between Brain Microstructure And Cognitive Impairment In Multiple Sclerosis. ISBI 2021: 685-688
[c28]
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  - conf/miccai/HarrisonLLICS21
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Josquin Harrison, Marco Lorenzi, Benoit Legghe, Xavier Iriart, Hubert Cochet, Maxime Sermesant:
Phase-Independent Latent Representation for Cardiac Shape Analysis. MICCAI (6) 2021: 537-546
2020
[c27]
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Marta Nuñez Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, Maxime Sermesant:
Estimation of Imaging Biomarker's Progression in Post-infarct Patients Using Cross-sectional Data. M&Ms and EMIDEC/STACOM@MICCAI 2020: 108-116
[c26]
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Santiago Silva, André Altmann, Boris Gutman, Marco Lorenzi:
Fed-BioMed: A General Open-Source Frontend Framework for Federated Learning in Healthcare. DART/DCL@MICCAI 2020: 201-210
[c25]
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Jaume Banus, Maxime Sermesant, Oscar Camara, Marco Lorenzi:
Joint Data Imputation and Mechanistic Modelling for Simulating Heart-Brain Interactions in Incomplete Datasets. MICCAI (6) 2020: 478-486
2019
[c24]
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Jaume Banus, Marco Lorenzi, Oscar Camara, Maxime Sermesant:
Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions. FIMH 2019: 285-293
[c23]
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Luigi Antelmi, Nicholas Ayache, Philippe Robert, Marco Lorenzi:
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. ICML 2019: 302-311
[c22]
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Sara Garbarino, Marco Lorenzi:
Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks. IPMI 2019: 57-69
[c21]
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Santiago Silva, Boris A. Gutman, Eduardo Romero, Paul M. Thompson, André Altmann, Marco Lorenzi:
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data. ISBI 2019: 270-274
[c20]
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Georgios Lazaridis, Marco Lorenzi, Sébastien Ourselin, David Garway-Heath:
Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Clinical Trials. MICCAI (1) 2019: 3-11
[c19]
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Razvan V. Marinescu, Marco Lorenzi, Stefano B. Blumberg, Alexandra L. Young, Pere Planell-Morell, Neil P. Oxtoby, Arman Eshaghi, Keir X. Yong, Sebastian J. Crutch, Polina Golland, Daniel C. Alexander:
Disease Knowledge Transfer Across Neurodegenerative Diseases. MICCAI (2) 2019: 860-868
2018
[c18]
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Marco Lorenzi, Maurizio Filippone:
Constraining the Dynamics of Deep Probabilistic Models. ICML 2018: 3233-3242
[c17]
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  - conf/miccai/NaderARL18
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Clément Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi:
Alzheimer's Disease Modelling and Staging Through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes. MLCN/DLF/iMIMIC@MICCAI 2018: 3-14
[c16]
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Luigi Antelmi, Nicholas Ayache, Philippe Robert, Marco Lorenzi:
Multi-channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease. MLCN/DLF/iMIMIC@MICCAI 2018: 15-23
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Juan Eugenio Iglesias, Marco Lorenzi, Sebastiano Ferraris, Loïc Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren:
Model-Based Refinement of Nonlinear Registrations in 3D Histology Reconstruction. MICCAI (2) 2018: 147-155
2017
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Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Timothy J. Shakespeare, Sebastian J. Crutch, Daniel C. Alexander:
A Vertex Clustering Model for Disease Progression: Application to Cortical Thickness Images. IPMI 2017: 134-145
2016
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Sebastiano Ferraris, Marco Lorenzi, Pankaj Daga, Marc Modat, Tom Vercauteren:
Accurate Small Deformation Exponential Approximant to Integrate Large Velocity Fields: Application to Image Registration. CVPR Workshops 2016: 457-464
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Marco Lorenzi, Boris Gutman, Derrek P. Hibar, André Altmann, Neda Jahanshad, Paul M. Thompson, Sébastien Ourselin:
Partial least squares modelling for imaging-genetics in Alzheimer's disease: Plausibility and generalization. ISBI 2016: 838-841
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Claire Cury, Marco Lorenzi, David M. Cash, Jennifer M. Nicholas, Alexandre Routier, Jonathan D. Rohrer, Sébastien Ourselin, Stanley Durrleman, Marc Modat:
Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease. SeSAMI@MICCAI 2016: 63-75
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Eliza Orasanu, Pierre-Louis Bazin, Andrew Melbourne, Marco Lorenzi, Hervé Lombaert, Nicola J. Robertson, Giles S. Kendall, Nikolaus Weiskopf, Neil Marlow, Sébastien Ourselin:
Longitudinal Analysis of the Preterm Cortex Using Multi-modal Spectral Matching. MICCAI (1) 2016: 255-263
2015
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Marco Lorenzi, Gabriel Ziegler, Daniel C. Alexander, Sébastien Ourselin:
Modelling Non-stationary and Non-separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution. MLMMI@ICML 2015: 35-44
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Boris A. Gutman, P. Thomas Fletcher, Manuel Jorge Cardoso, Greg M. Fleishman, Marco Lorenzi, Paul M. Thompson, Sébastien Ourselin:
A Riemannian Framework for Intrinsic Comparison of Closed Genus-Zero Shapes. IPMI 2015: 205-218
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Marco Lorenzi, Gabriel Ziegler, Daniel C. Alexander, Sébastien Ourselin:
Efficient Gaussian Process-Based Modelling and Prediction of Image Time Series. IPMI 2015: 626-637
2014
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Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, Xavier Pennec:
A Biophysical Model of Shape Changes due to Atrophy in the Brain with Alzheimer's Disease. MICCAI (2) 2014: 41-48
2013
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Marco Lorenzi, Xavier Pennec:
Parallel Transport with Pole Ladder: Application to Deformations of Time Series of Images. GSI 2013: 68-75
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Marco Lorenzi, Bjoern H. Menze, Marc Niethammer, Nicholas Ayache, Xavier Pennec:
Sparse Scale-Space Decomposition of Volume Changes in Deformations Fields. MICCAI (2) 2013: 328-335
2012
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Marco Lorenzi, Nicholas Ayache, Xavier Pennec:
Regional Flux Analysis of Longitudinal Atrophy in Alzheimer's Disease. MICCAI (1) 2012: 739-746
2011
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Marco Lorenzi, Nicholas Ayache, Xavier Pennec:
Schild's Ladder for the Parallel Transport of Deformations in Time Series of Images. IPMI 2011: 463-474
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Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, Xavier Pennec:
Mapping the Effects of Aβ 1 - 42 Levels on the Longitudinal Changes in Healthy Aging: Hierarchical Modeling Based on Stationary Velocity Fields. MICCAI (2) 2011: 663-670

Informal and Other Publications

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2024
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Riccardo Taiello, Melek Önen, Clémentine Gritti, Marco Lorenzi:
Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Client Stragglers. IACR Cryptol. ePrint Arch. 2024: 942 (2024)
2023
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  - journals/corr/abs-2304-08054
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Irene Balelli, Aude Sportisse, Francesco Cremonesi, Pierre-Alexandre Mattei, Marco Lorenzi:
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models. CoRR abs/2304.08054 (2023)
[i22]
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  - journals/corr/abs-2304-12012
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Francesco Cremonesi, Marc Vesin, Sergen Cansiz, Yannick Bouillard, Irene Balelli, Lucia Innocenti, Santiago Silva, Samy-Safwan Ayed, Riccardo Taiello, Laetitia Kameni, Richard Vidal, Fanny Orlhac, Christophe Nioche, Nathan Lapel, Bastien Houis, Romain Modzelewski, Olivier Humbert, Melek Önen, Marco Lorenzi:
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications. CoRR abs/2304.12012 (2023)
[i21]
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  - journals/corr/abs-2306-02658
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Etrit Haxholli, Marco Lorenzi:
Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching. CoRR abs/2306.02658 (2023)
[i20]
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  - journals/corr/abs-2306-02731
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Etrit Haxholli, Marco Lorenzi:
Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows. CoRR abs/2306.02731 (2023)
[i19]
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  - journals/corr/abs-2306-02807
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Etrit Haxholli, Marco Lorenzi:
On Tail Decay Rate Estimation of Loss Function Distributions. CoRR abs/2306.02807 (2023)
[i18]
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  - journals/corr/abs-2309-07352
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André Altmann, Ana C. Lawry Aguila, Neda Jahanshad, Paul M. Thompson, Marco Lorenzi:
Tackling the dimensions in imaging genetics with CLUB-PLS. CoRR abs/2309.07352 (2023)
[i17]
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Lucia Innocenti, Michela Antonelli, Francesco Cremonesi, Kenaan Sarhan, Alejandro Granados, Vicky Goh, Sébastien Ourselin, Marco Lorenzi:
Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation. CoRR abs/2309.17097 (2023)
2022
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Irene Balelli, Santiago Silva, Marco Lorenzi:
A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations. CoRR abs/2204.07352 (2022)
[i15]
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  - journals/corr/abs-2205-10120
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Riccardo Taiello, Melek Önen, Olivier Humbert, Marco Lorenzi:
Privacy Preserving Image Registration. CoRR abs/2205.10120 (2022)
[i14]
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  - journals/corr/abs-2206-10189
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. CoRR abs/2206.10189 (2022)
[i13]
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Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux:
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR abs/2210.04620 (2022)
[i12]
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization. CoRR abs/2211.11656 (2022)
2021
[i11]
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  - journals/corr/abs-2101-09321
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Vien Ngoc Dang, Giuseppe Di Giacomo, Viola Marconetto, Prateek Mathur, Rosa Cortese, Marco Lorenzi, Ferran Prados, Maria A. Zuluaga:
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation. CoRR abs/2101.09321 (2021)
[i10]
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  - journals/corr/abs-2104-14873
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Adrià Casamitjana, Marco Lorenzi, Sebastiano Ferraris, Loïc Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren, Juan Eugenio Iglesias:
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas. CoRR abs/2104.14873 (2021)
[i9]
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning. CoRR abs/2105.05883 (2021)
[i8]
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  - journals/corr/abs-2107-12211
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Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi:
On The Impact of Client Sampling on Federated Learning Convergence. CoRR abs/2107.12211 (2021)
2020
[i7]
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  - journals/corr/abs-2006-11901
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Yann Fraboni, Richard Vidal, Marco Lorenzi:
Free-rider Attacks on Model Aggregation in Federated Learning. CoRR abs/2006.11901 (2020)
[i6]
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  - journals/corr/abs-2010-01052
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Jaume Banus, Maxime Sermesant, Oscar Camara, Marco Lorenzi:
Joint data imputation and mechanistic modelling for simulating heart-brain interactions in incomplete datasets. CoRR abs/2010.01052 (2020)
2019
[i5]
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  - journals/corr/abs-1901-03517
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Razvan V. Marinescu, Marco Lorenzi, Stefano B. Blumberg, Alexandra L. Young, Pere P. Morell, Neil P. Oxtoby, Arman Eshaghi, Keir X. Yong, Sebastian J. Crutch, Daniel C. Alexander:
Disease Knowledge Transfer across Neurodegenerative Diseases. CoRR abs/1901.03517 (2019)
[i4]
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  - journals/corr/abs-1901-03553
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Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Sebastian J. Crutch, Daniel C. Alexander:
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. CoRR abs/1901.03553 (2019)
[i3]
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  - journals/corr/abs-1902-10952
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Clément Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi:
Monotonic Gaussian Process for Spatio-Temporal Trajectory Separation in Brain Imaging Data. CoRR abs/1902.10952 (2019)
[i2]
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  - journals/corr/abs-1905-09826
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Raphaël Sivera, Hervé Delingette, Marco Lorenzi, Xavier Pennec, Nicholas Ayache:
A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments. CoRR abs/1905.09826 (2019)
2018
[i1]
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  - journals/corr/abs-1810-08553
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Santiago Silva, Boris Gutman, Eduardo Romero, Paul M. Thompson, André Altmann, Marco Lorenzi:
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data. CoRR abs/1810.08553 (2018)

Coauthor Index

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