Schild's Ladder for the Parallel Transport of Deformations in Time Series of Images. - Marco Lorenzi; Nicholas Ayache; Xavier Pennec (IPMI, 2011)

Mapping the Effects of Aβ 1 - 42 Levels on the Longitudinal Changes in Healthy Aging: Hierarchical Modeling Based on Stationary Velocity Fields. - Marco Lorenzi; Nicholas Ayache; Giovanni B. Frisoni; Xavier Pennec (MICCAI (2), 2011)

Regional Flux Analysis of Longitudinal Atrophy in Alzheimer's Disease. - Marco Lorenzi; Nicholas Ayache; Xavier Pennec (MICCAI (1), 2012)

Deformation-based morphometry of the brain for the development of surrogate markers in Alzheimer's disease. - Marco Lorenzi (2012)

Parallel Transport with Pole Ladder: Application to Deformations of Time Series of Images. - Marco Lorenzi; Xavier Pennec (GSI, 2013)

Sparse Scale-Space Decomposition of Volume Changes in Deformations Fields. - Marco Lorenzi; Bjoern H. Menze; Marc Niethammer; Nicholas Ayache; Xavier Pennec (MICCAI (2), 2013)

Geodesics, Parallel Transport & One-Parameter Subgroups for Diffeomorphic Image Registration. - Marco Lorenzi; Xavier Pennec (Int. J. Comput. Vis., 2013)

LCC-Demons: A robust and accurate symmetric diffeomorphic registration algorithm. - Marco Lorenzi; Nicholas Ayache; Giovanni B. Frisoni; Xavier Pennec (NeuroImage, 2013)

A Biophysical Model of Shape Changes due to Atrophy in the Brain with Alzheimer's Disease. - Bishesh Khanal; Marco Lorenzi; Nicholas Ayache; Xavier Pennec (MICCAI (2), 2014)

Efficient Parallel Transport of Deformations in Time Series of Images: From Schild's to Pole Ladder. - Marco Lorenzi; Xavier Pennec (J. Math. Imaging Vis., 2014)

Modelling Non-stationary and Non-separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution. - Marco Lorenzi; Gabriel Ziegler; Daniel C. Alexander; Sébastien Ourselin (MLMMI@ICML, 2015)

A Riemannian Framework for Intrinsic Comparison of Closed Genus-Zero Shapes. - Boris A. Gutman; P. Thomas Fletcher; Manuel Jorge Cardoso; Greg M. Fleishman; Marco Lorenzi; Paul M. Thompson; Sébastien Ourselin (IPMI, 2015)

Efficient Gaussian Process-Based Modelling and Prediction of Image Time Series. - Marco Lorenzi; Gabriel Ziegler; Daniel C. Alexander; Sébastien Ourselin (IPMI, 2015)

Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge. - David M. Cash; Chris Frost 001; Leonardo O. Iheme; Devrim Ünay; Melek Kandemir; Jurgen Fripp; Olivier Salvado; Pierrick Bourgeat; Martin Reuter 001; Bruce Fischl; Marco Lorenzi; Giovanni B. Frisoni; et al. (NeuroImage, 2015)

Regional flux analysis for discovering and quantifying anatomical changes: An application to the brain morphometry in Alzheimer's disease. - Marco Lorenzi; Nicholas Ayache; Xavier Pennec (NeuroImage, 2015)

Accurate Small Deformation Exponential Approximant to Integrate Large Velocity Fields: Application to Image Registration. - Sebastiano Ferraris; Marco Lorenzi; Pankaj Daga; Marc Modat; Tom Vercauteren (CVPR Workshops, 2016)

Partial least squares modelling for imaging-genetics in Alzheimer's disease: Plausibility and generalization. - Marco Lorenzi; Boris Gutman; Derrek P. Hibar; André Altmann; Neda Jahanshad; Paul M. Thompson; Sébastien Ourselin (ISBI, 2016)

Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease. - Claire Cury; Marco Lorenzi; David M. Cash; Jennifer M. Nicholas; Alexandre Routier; Jonathan D. Rohrer; Sébastien Ourselin; Stanley Durrleman; Marc Modat (SeSAMI@MICCAI, 2016)

Longitudinal Analysis of the Preterm Cortex Using Multi-modal Spectral Matching. - Eliza Orasanu; Pierre-Louis Bazin; Andrew Melbourne; Marco Lorenzi; Hervé Lombaert; Nicola J. Robertson; Giles S. Kendall; Nikolaus Weiskopf; Neil Marlow; Sébastien Ourselin (MICCAI (1), 2016)

A biophysical model of brain deformation to simulate and analyze longitudinal MRIs of patients with Alzheimer's disease. - Bishesh Khanal; Marco Lorenzi; Nicholas Ayache; Xavier Pennec (NeuroImage, 2016)

A Vertex Clustering Model for Disease Progression: Application to Cortical Thickness Images. - Razvan V. Marinescu; Arman Eshaghi; Marco Lorenzi; Alexandra L. Young; Neil P. Oxtoby; Sara Garbarino; Timothy J. Shakespeare; Sebastian J. Crutch; Daniel C. Alexander (IPMI, 2017)

Constraining the Dynamics of Deep Probabilistic Models. - Marco Lorenzi; Maurizio Filippone (ICML, 2018)

Multi-channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease. - Luigi Antelmi; Nicholas Ayache; Philippe Robert; Marco Lorenzi (MLCN/DLF/iMIMIC@MICCAI, 2018)

Model-Based Refinement of Nonlinear Registrations in 3D Histology Reconstruction. - Juan Eugenio Iglesias; Marco Lorenzi; Sebastiano Ferraris; Loïc Peter; Marc Modat; Allison Stevens; Bruce Fischl; Tom Vercauteren (MICCAI (2), 2018)

Alzheimer's Disease Modelling and Staging Through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes. - Clément Abi Nader; Nicholas Ayache; Philippe Robert; Marco Lorenzi (MLCN/DLF/iMIMIC@MICCAI, 2018)

A magnetic resonance multi-atlas for the neonatal rabbit brain. - 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 (NeuroImage, 2018)

Susceptibility of brain atrophy to TRIB3 in Alzheimer's disease, evidence from functional prioritization in imaging genetics. - 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 (Proc. Natl. Acad. Sci. USA, 2018)

Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions. - Jaume Banus; Marco Lorenzi; Oscar Camara 001; Maxime Sermesant (FIMH, 2019)

Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. - Luigi Antelmi; Nicholas Ayache; Philippe Robert; Marco Lorenzi (ICML, 2019)

Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks. - Sara Garbarino; Marco Lorenzi (IPMI, 2019)

Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data. - Santiago Silva 001; Boris A. Gutman; Eduardo Romero 001; Paul M. Thompson; André Altmann; Marco Lorenzi (ISBI, 2019)

Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Clinical Trials. - Georgios Lazaridis; Marco Lorenzi; Sébastien Ourselin; David Garway-Heath (MICCAI (1), 2019)

Disease Knowledge Transfer Across Neurodegenerative Diseases. - 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 (MICCAI (2), 2019)

Disease Knowledge Transfer across Neurodegenerative Diseases. - 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 (CoRR, 2019)

Monotonic Gaussian Process for Spatio-Temporal Trajectory Separation in Brain Imaging Data. - Clément Abi Nader; Nicholas Ayache; Philippe Robert; Marco Lorenzi (CoRR, 2019)

Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort. - 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; et al. (NeuroImage, 2019)

Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease. - Marco Lorenzi; Maurizio Filippone; Giovanni B. Frisoni; Daniel C. Alexander; Sébastien Ourselin (NeuroImage, 2019)

DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. - Razvan V. Marinescu; Arman Eshaghi; Marco Lorenzi; Alexandra L. Young; Neil P. Oxtoby; Sara Garbarino; Sebastian J. Crutch; Daniel C. Alexander (NeuroImage, 2019)

A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments. - Raphaël Sivera; Hervé Delingette; Marco Lorenzi; Xavier Pennec; Nicholas Ayache (NeuroImage, 2019)

Modelling pathological processes from heterogeneous and high-dimensional biomedical data. - Marco Lorenzi (2020)

Joint Data Imputation and Mechanistic Modelling for Simulating Heart-Brain Interactions in Incomplete Datasets. - Jaume Banus; Maxime Sermesant; Oscar Camara 001; Marco Lorenzi (MICCAI (6), 2020)

Estimation of Imaging Biomarker's Progression in Post-infarct Patients Using Cross-sectional Data. - Marta Nuñez Garcia; Nicolas Cedilnik; Shuman Jia; Hubert Cochet; Marco Lorenzi; Maxime Sermesant (M&Ms and EMIDEC/STACOM@MICCAI, 2020)

Fed-BioMed: A General Open-Source Frontend Framework for Federated Learning in Healthcare. - Santiago Silva 001; André Altmann; Boris Gutman; Marco Lorenzi (DART/DCL@MICCAI, 2020)

Monotonic Gaussian Process for spatio-temporal disease progression modeling in brain imaging data. - Clément Abi Nader; Nicholas Ayache; Philippe Robert; Marco Lorenzi; Alzheimer's Disease Neuroimaging Initiative (NeuroImage, 2020)

Free-rider Attacks on Model Aggregation in Federated Learning. - Yann Fraboni; Richard Vidal; Marco Lorenzi (AISTATS, 2021)

Disentangling the association between genetics and functional connectivity in Mild Cognitive Impairment. - Heba Elshatoury; Federica Cruciani; Francesco Zumerle; Silvia Francesca Storti; André Altmann; Marco Lorenzi; Gholamreza Anbarjafari; Gloria Menegaz; Ilaria Boscolo Galazzo (BHI, 2021)

Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning. - Yann Fraboni; Richard Vidal; Laetitia Kameni; Marco Lorenzi (ICML, 2021)

A Probabilistic Framework for Modeling the Variability Across Federated Datasets. - Irene Balelli; Santiago Silva 001; Marco Lorenzi (IPMI, 2021)

Multivariate Data Analysis Suggests The Link Between Brain Microstructure And Cognitive Impairment In Multiple Sclerosis. - Lorenza Brusini; Federica Cruciani; Ilaria Boscolo Galazzo; Marco Pitteri; Silvia Francesca Storti; Massimiliano Calabrese; Marco Lorenzi; Gloria Menegaz (ISBI, 2021)

Phase-Independent Latent Representation for Cardiac Shape Analysis. - Josquin Harrison; Marco Lorenzi; Benoit Legghe; Xavier Iriart; Hubert Cochet; Maxime Sermesant (MICCAI (6), 2021)

Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation. - Vien Ngoc Dang; Giuseppe Di Giacomo; Viola Marconetto; Prateek Mathur; Rosa Cortese; Marco Lorenzi; Ferran Prados; Maria A. Zuluaga (CoRR, 2021)

On The Impact of Client Sampling on Federated Learning Convergence. - Yann Fraboni; Richard Vidal; Laetitia Kameni; Marco Lorenzi (CoRR, 2021)

Biophysics-based statistical learning: Application to heart and brain interactions. - Jaume Banus; Marco Lorenzi; Oscar Camara 001; Maxime Sermesant (Medical Image Anal., 2021)

Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks. - Georgios Lazaridis; Marco Lorenzi; Sébastien Ourselin; David Garway-Heath (Medical Image Anal., 2021)

Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain. - Sara Garbarino; Marco Lorenzi; Alzheimer's Disease Neuroimaging Initiative (NeuroImage, 2021)

What PLS can still do for Imaging Genetics in Alzheimer's disease. - Federica Cruciani; André Altmann; Marco Lorenzi; Gloria Menegaz; Ilaria Boscolo Galazzo (BHI, 2022)

A General Theory for Client Sampling in Federated Learning. - Yann Fraboni; Richard Vidal; Laetitia Kameni; Marco Lorenzi (FL@IJCAI, 2022)

Privacy Preserving Image Registration. - Riccardo Taiello; Melek Önen; Olivier Humbert; Marco Lorenzi (MICCAI (6), 2022)

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. - Jean Ogier du Terrail; Samy-Safwan Ayed; Edwige Cyffers; Felix Grimberg; Chaoyang He 001; Regis Loeb; Paul Mangold; Tanguy Marchand; Othmane Marfoq; Erum Mushtaq; Boris Muzellec; Constantin Philippenko; et al. (NeurIPS, 2022)

A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations. - Irene Balelli; Santiago Silva 001; Marco Lorenzi (CoRR, 2022)

Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization. - Yann Fraboni; Richard Vidal; Laetitia Kameni; Marco Lorenzi (CoRR, 2022)

Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas. - Adrià Casamitjana; Marco Lorenzi; Sebastiano Ferraris; Loïc Peter; Marc Modat; Allison Stevens; Bruce Fischl; Tom Vercauteren; Juan Eugenio Iglesias (Medical Image Anal., 2022)

Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation. - Vien Ngoc Dang; Francesco Galati; Rosa Cortese; Giuseppe Di Giacomo; Viola Marconetto; Prateek Mathur; Karim Lekadir; Marco Lorenzi; Ferran Prados; Maria A. Zuluaga (Medical Image Anal., 2022)

Predicting myocardial infarction through retinal scans and minimal personal information. - Andres Diaz-Pinto; Nishant Ravikumar; Rahman Attar; Avan Suinesiaputra; Yitian Zhao; Eylem Levelt; Erica Dall' Armellina; Marco Lorenzi; Qingyu Chen 001; Tiarnan D. L. Keenan; Elvira Agrón; Emily Y. Chew; et al. (Nat. Mach. Intell., 2022)

Validation of Federated Unlearning on Collaborative Prostate Segmentation. - Yann Fraboni; Lucia Innocenti; Michela Antonelli; Richard Vidal; Laetitia Kameni; Sébastien Ourselin; Marco Lorenzi (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation. - Lucia Innocenti; Michela Antonelli; Francesco Cremonesi; Kenaan Sarhan; Alejandro Granados; Vicky Goh; Sébastien Ourselin; Marco Lorenzi (PKDD/ECML Workshops (4), 2023)

Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models. - Irene Balelli; Aude Sportisse; Francesco Cremonesi; Pierre-Alexandre Mattei; Marco Lorenzi (CoRR, 2023)

Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications. - Francesco Cremonesi; Marc Vesin; Sergen Cansiz; Yannick Bouillard; Irene Balelli; Lucia Innocenti; Santiago Silva 001; Samy-Safwan Ayed; Riccardo Taiello; Laetitia Kameni; Richard Vidal; Fanny Orlhac; et al. (CoRR, 2023)

Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching. - Etrit Haxholli; Marco Lorenzi (CoRR, 2023)

Enhanced Distribution Modelling via Augmented Architectures For Neural ODE Flows. - Etrit Haxholli; Marco Lorenzi (CoRR, 2023)

Tackling the dimensions in imaging genetics with CLUB-PLS. - André Altmann; Ana C. Lawry Aguila; Neda Jahanshad; Paul M. Thompson; Marco Lorenzi (CoRR, 2023)

A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. - Yann Fraboni; Richard Vidal; Laetitia Kameni; Marco Lorenzi (J. Mach. Learn. Res., 2023)

MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer's disease progression modelling. - Gerard Martí-Juan; Marco Lorenzi; Gemma Piella; Alzheimer's Disease Neuroimaging Initiative (NeuroImage, 2023)

Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Stragglers. - Riccardo Taiello; Melek Önen; Clémentine Gritti; Marco Lorenzi (ARES, 2024)

SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization. - Yann Fraboni; Martin Van Waerebeke; Kevin Scaman; Richard Vidal; Laetitia Kameni; Marco Lorenzi (AISTATS, 2024)

Federated Multi-centric Image Segmentation with Uneven Label Distribution. - Francesco Galati; Rosa Cortese; Ferran Prados; Marco Lorenzi; Maria A. Zuluaga (MICCAI (10), 2024)

Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications. - Riccardo Taiello; Sergen Cansiz; Marc Vesin; Francesco Cremonesi; Lucia Innocenti; Melek Önen; Marco Lorenzi (ISIC/iMIMIC/EARTH/DeCaF@MICCAI, 2024)

Disease Progression Modelling and Stratification for Detecting Sub-trajectories in the Natural History of Pathologies: Application to Parkinson's Disease Trajectory Modelling. - Alessandro Viani; Boris A. Gutman; Emile d'Angremont; Marco Lorenzi (LDTM/MMMI/ML4MHD/ML-CDS@MICCAI, 2024)

A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications. - Francesco Cremonesi; Lucia Innocenti; Sébastien Ourselin; Vicky Goh; Michela Antonelli; Marco Lorenzi (CoRR, 2024)

Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Client Stragglers. - Riccardo Taiello; Melek Önen; Clémentine Gritti; Marco Lorenzi (IACR Cryptol. ePrint Arch., 2024)

On Tail Decay Rate Estimation of Loss Function Distributions. - Etrit Haxholli; Marco Lorenzi (J. Mach. Learn. Res., 2024)

Privacy preserving image registration. - Riccardo Taiello; Melek Önen; Francesco Capano; Olivier Humbert; Marco Lorenzi (Medical Image Anal., 2024)

Buffalo: A Practical Secure Aggregation Protocol for Buffered Asynchronous Federated Learning. - Riccardo Taiello; Clémentine Gritti; Melek Önen; Marco Lorenzi (CODASPY, 2025)

Buffalo: A Practical Secure Aggregation Protocol for Asynchronous Federated Learning. - Riccardo Taiello; Clémentine Gritti; Melek Önen; Marco Lorenzi (IACR Cryptol. ePrint Arch., 2025)

A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures. - Marco Corneli; Elena Erosheva; Xunlei Qian; Marco Lorenzi (Comput. Stat., 2025)

When to Forget? Complexity Trade-offs in Machine Unlearning. - Martin Van Waerebeke; Marco Lorenzi; Giovanni Neglia; Kevin Scaman (CoRR, 2025)