Gerard Martí-Juan, Marco Lorenzi, Gemma Piella. MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling. NeuroImage: 119892, 2023.
Irene Balelli, Santiago Silva, and Marco Lorenzi. A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations. Journal of Machine Learning for Biomedical Imaging, 2022.
Clement Abi Nader, Federica Ribaldi, Giovanni B. Frisoni, Valentina Garibotto, Philippe Robert, Nicholas Ayache, and Marco Lorenzi. SimulAD: a dynamical model for personalized simulation and disease staging in Alzheimer’s disease. Neurobiology of Aging 113: 73-83, 2022.
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. Nature Machine Intelligence 4, no. 1: 55-61, 2022.
Sara Garbarino and Marco Lorenzi. Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain. NeuroImage, 235, 117980, 2021.
Georgios Lazaridis, Giovanni Montesano, Saman Sadeghi Afgeh, Jibran Mohamed-Noriega, Sebastien Ourselin, Marco Lorenzi, and David F. Garway-Heath. Predicting visual fields from optical coherence tomography via an ensemble of deep representation learners. American journal of ophthalmology 238: 52-65, 2022.
Giorgos Lazaridis, Marco Lorenzi, Jibran Mohamed-Noriega, Soledad Aguilar-Munoa, Katsuyoshi Suzuki, Hiroki Nomoto, Sebastien Ourselin, David F. Garway-Heath. OCT signal enhancement with deep learning. Ophthalmology Glaucoma, 4(3), 295-304, 2021.
Peter A. Wijeratne, Sara Garbarino, Sarah Gregory, Eileanoir B. Johnson, Rachael I. Scahill, Jane S. Paulsen, Sarah J. Tabrizi, Marco Lorenzi, and Daniel C. Alexander. Revealing the timeline of structural MRI changes in premanifest to manifest Huntington disease. Neurology Genetics 7:5, 2021.
Clément Abi Nader, Nicholas Ayache, Giovanni Frisoni, Philippe Robert, Marco Lorenzi. Simulating the outcome of amyloid treatments in Alzheimer's Disease from multi–modal imaging and clinical data. Brain Communications, Oxford University Press, 2021.
Vien Ngoc Dang, Francesco Galati, Rosa Cortese, et al. Vessel–CAPTCHA: an efficient learning framework for vessel annotation and segmentation. 2021. Medical Image Analysis, Elsevier, 2021
Jaume Banus, Marco Lorenzi, Oscar Camara, Maxime Sermesant. Biophysics–based statistical learning: Application to heart and brain interactions. Medical Image Analysis, Elsevier, 2021
Adrià Casamitjana; Marco Lorenzi, et al, Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas, Medical Image Analysis, 2021
Lazaridis, Georgios; Lorenzi, Marco; Ourselin, Sebastien; Garway-Heath, David; Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks, Medical Image Analysis, 68, 101906, 2021
Clément Abi Nader, Nicholas Ayache, Philippe Robert and Marco Lorenzi. Monotonic Gaussian Process for spatio-temporal disease progression modeling in brain imaging data. NeuroImage, Volume 205, 15 January 2020, 116266.
Raphaël Sivera, Nicolas Capet, Valeria Manera, Roxane Fabre, Marco Lorenzi, et al.. Voxel–based assessments of treatment effects on longitudinal brain changes in the Multidomain Alzheimer Preventive Trial cohort. Neurobiology of Aging, Elsevier, 2020, 94, pp.50–59
Sara Garbarino, Marco Lorenzi, et al; Differences in topological progression profile among neurodegenerative diseases from imaging data, Elife, 8, e49298, 2019
Raphael 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. 2019 Sep;198:255-270.
Claire Cury, Stanley Durrleman, David Cash, Marco Lorenzi, Jennifer Nicholas, et al. Spatiotemporal Analysis for Detection of Pre-symptomatic Shape Changes in Neurodegenerative diseases: applied to GENFI study. NeuroImage, Volume 188, March 2019, Pages 282-290.
Sebastiano Ferraris , Hannes van der Merle, Lennart Van Der Veeken, Herran 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, Volume 179, Pages 187-198.
Marzia A Scelsi, Raiyan R Khan, Marco Lorenzi, Leigh Christopher, Michael D Greicius, Jonathan M Schott, Sebastien Ourselin, Andre Altmann . Genetic study of multimodal imaging Alzheimer’s disease progression score implicates novel loci. Brain, Volume 141, Issue 7, 1 July 2018, Pages 2167–2180
Marco Lorenzi, Andre Altmann, Boris Gutman, Selina Wray, Charles Arber, Derrek P. Hibar, Neda Jahanshad, Jonathan M. Schott, Daniel C. Alexander, Paul M. Thompson and Sebastien Ourselin. Susceptibility of brain atrophy to TRIB3 in Alzheimer's disease: Evidence from functional prioritization in imaging genetics. Proceedings of the National Academy of Sciences of the United States of America (PNAS). March 20, 2018. 115 (12) 3162-3167.
Marco Lorenzi, Maurizio Filippone, Giovanni B. Frisoni, Daniel C. Alexander, Sebastien Ourselin. Probabilistic disease progression modeling to characterize diagnostic uncertainty: application to staging and prediction in Alzheimer's disease. NeuroImage, S1053-8119(17)30706-1, 2017.
Alex F. Mendelson, Maria A. Zuluaga, Marco Lorenzi, Brian F. Hutton, Sebastien Ourselin, (2017). Selection bias in the reported performances of AD classification pipelines. NeuroImage: Clinical, 14, 400-416, 2017.
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, 2017.
Mehdi Hadj-Hamou, Marco Lorenzi, Nicholas Ayache, Xavier Pennec. Longitudinal analysis of image time series with diffeomorphic deformations: a computational framework based on stationary velocity fields. Frontiers in Neuroscience, 10, 236, 2016.
Marco Lorenzi , Ivor J. Simpson, Alex F. Mendelson, Sjoerd B. Vos, M. Jorge Cardoso, Marc Modat, Jonathan Schott, Sebastien Ourselin. Multimodal Image Analysis in Alzheimer's Disease via Statistical Modelling of Non-local Intensity Correlations. Scientific Reports (NPG), 6, 2261, 2016.
David M. Cash, Chris Frost, Leonardo O. Iheme, Devrim Unay, Melek Kandemir, Jurgen Fripp, Olivier Salvado, Pierrick Bourgeat, Martin Reuter, Bruce Fischl, Marco Lorenzi, Giovanni B. Frisoni, Xavier Pennec, Ronald K. Pierson, et al. Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge. NeuroImage, 123: 149-164, 2015.
Marco Lorenzi , Nicholas Ayache and 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.
Marco Lorenzi, Xavier Pennec, Giovanni B. Frisoni and Nicholas Ayache. Disentangling Normal Aging from Alzheimer's Disease in Structural MR Images. Neurobiology of Aging, 36:S42-S52, 2015.
Antonello Preti, Cristina Muscio, Marina Boccardi, Marco Lorenzi, Giovanni de Girolamo, Giovanni B. Frisoni. Impact of alcohol consumption in healthy adults: A magnetic resonance imaging investigation. Psychiatry Research: Neuroimaging, 224 (2), 96-103, 2014.
Marco Lorenzi and Xavier Pennec. Efficient Parallel Transport of Deformations in Time Series of Images: from Schild's to Pole Ladder. Journal of Mathematical Imaging and Vision, 50(1-2):5-17, 2014.
Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and Xavier Pennec. LCC-Demons: a robust and accurate symmetric diffeomorphic registration algorithm. NeuroImage, 81(1):470-483, 2013.
Marco Lorenzi and Xavier Pennec. Geodesics, Parallel Transport & One-parameter Subgroups for Diffeomorphic Image Registration. International Journal of Computer Vision, 105(2):111-127, 2013.
Roberta Rossi, Michela Pievani, Marco Lorenzi, Marina Boccardi, Rossella Beneduce, Stefano Bignotti, Genoveffa Borsci, Maria Cotelli, Panteleimon Giannakopoulos, Laura R. Magni, Luciana Rillosi, Sandra Rosini, Giuseppe Rossi, and Giovanni B. Frisoni. Structural brain features of borderline personality and bipolar disorders. Psychiatry Research: Neuroimaging, 213(2):83-91, 2013.
Marco Lorenzi, Alberto Beltramello, Nicola Mercuri, Elisa Canu, Giada Zoccatelli, Francesca Pizzini, Franco Alessandrini, Maria Cotelli, Sandra Rosini, Daniela Costardi, Carlo Caltagirone, and Giovanni B. Frisoni. Effect of memantine on resting state default mode network activity in Alzheimer's disease. Drugs and Aging, 28(3):205-217, 2011.
Marco Lorenzi, Michael Donohue, Donata Paternico, Cristina Scarpazza, Susanne Ostrowitzki, Olivier Blin, Elaine Irving, and Giovanni B. Frisoni. Enrichment through biomarkers in clinical trials of Alzheimer's drugs in patients with mild cognitive impairment. Neurobiology of Aging, 31(8):1443-1451, 2010.
Anna Caroli, Marco Lorenzi, Cristina Geroldi, Flavio Nobili, Barbara Paghera, Mario Bonetti, Maria Cotelli, Giovanni B. Frisoni. Metabolic compensation and depression in Alzheimer's disease. Dementia and geriatric cognitive disorders, 29(1):37-45, 2010.
Giovanni B. Frisoni, Marco Lorenzi, Anna Caroli, Nina Kemppainen, Kjell Nagren, and Juha O. Rinne. In vivo mapping of amyloid toxicity in Alzheimer's disease. Neurology, 72(17): 1504-1511, 2009.
Reviewed international conferences with proceedings
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 Teleńczuk, 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. In NeurIPS, Datasets and Benchmarks Track. 2022.
Yann Fraboni, Richard Vidal, Laetitia Kameni, and Marco Lorenzi. A General Theory for Client Sampling in Federated Learning. In International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI (FL-IJCAI'22). 2022.
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi. Clustered Sampling: Low–Variance and Improved Representativity for Clients Selection in Federated Learning. International Conference on Machine Learning, ICML, 2021
Yann Fraboni, Richard Vidal, Marco Lorenzi. Free–rider Attacks on Model Aggregation in Federated Learning. AISTATS 2021 – 24th International Conference on Artificial Intelligence and Statistics, Apr 2021.
Irene Balelli, Santiago Silva, Marco Lorenzi. A Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi–View Observations. International Conference on Information Processing in Medical Imaging, 701-714, 2021
Santiago Silva, Andre Altmann, Boris Gutman, Marco Lorenzi. Fed–BioMed: A general open–source frontendframework for federated learning in healthcare. 1st Workshop on Distributed and Collaborative Learning, Oct 2020, Lima, Peru. pp.201–210.
Jaume Banus, Maxime Sermesant, Oscar Camara, Marco Lorenzi. Joint data imputation and mechanistic modelling for simulating heart–brain interactions in incomplete datasets. MICCAI 2020 – 23th International Conference on Medical Image Computing and Computer Assisted Intervention, Oct 2020
Josquin Harrison; Marco Lorenzi; Benoit Legghe, Xavier Iriart, Hubert Cochet, Maxime Sermesant, Phase-Independent Latent Representation for Cardiac Shape Analysis, International Conference on Medical Image Computing and Computer-Assisted Intervention, 537-546, 2021
Marta Nuñez–Garcia, Nicolas Cedilnik, Shuman Jia, Hubert Cochet, Marco Lorenzi, et al. Estimation of imaging biomarker's progression in post–infarct patients using cross–sectional data. STACOM 2020
Luigi Antelmi, Nicholas Ayache, Philippe Robert and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. Proceedings of the 36th International Conference on Machine Learning (ICML). Acceptance rate: ~20%.
Sara Garbarino, Marco Lorenzi. Modeling and inference of spatio–temporal protein dynamics across brain networks. IPMI 2019 – International Conference on Information Processing in Medical Imaging, Jun 2019, Hong Kong, Hong Kong SAR China. pp.57–69
Jaume Banus Cobo, Marco Lorenzi, Oscar Camara, Maxime Sermesant. Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions. Proceedings of the 10th International Conference on Functional Imaging and Modeling of the Heart (FIMH).
Santiago Silva, Boris Gutman, Barbara Bardoni, Paul M Thompson, Andre Altmann, Marco
Lorenzi. Multivariate Learning in Distributed Biomedical Databases: Meta-analysis of Large-scale Brain Imaging Data. IEEE International Symposium on Biomedical Imaging (ISBI), Venice, 2019.
Lazaridis, Georgios; Lorenzi, Marco; Ourselin, Sebastien; Garway-Heath, David; Enhancing OCT signal by fusion of GANs: Improving statistical power of glaucoma clinical trials, International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019
Marco Lorenzi, Maurizio Filippone. Constraining the Dynamics of Deep Probabilistic Models. Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80:3233-3242, 2018. Note: Oral podium presentation. Acceptance rate: ~25%.
Juan Eugenio Iglesias, Marco Lorenzi, Sebastiano Ferraris, Loic Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren: "Model-based refinement of nonlinear registrations in 3D histology reconstruction", MICCAI 2018. Acceptance rate: ~25%.
Răzvan Valentin 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. Information Processing in Medical Imaging (IPMI), 10265: 134-145, Springer, LNCS, 2017. Note: Oral podium presentation. Acceptance rate: ~30%
Marco Lorenzi, Boris Gutman, Paul M Thompson, Daniel C Alexander, Sebastien Ourselin, Andre Altmann. Secure multivariate large-scale multi-centric analysis through on-line learning: an imaging genetics case study. 12th International Symposium on Medical Information Processing and Analysis, 1016016, International Society for Optics and Photonics, 2017. Note: Oral podium presentation
Eliza Orasanu, Pierre-Louis Bazin, Andrew Melbourne, Marco Lorenzi, Herve Lombaert, Nicola J Robertson, Giles Kendall, Nikolaus Weiskopf, Neil Marlow, Sebastien Ourselin. Longitudinal analysis of the preterm cortex using multi-modal spectral matching. Medical Image Computing and Computer Aided Intervention (MICCAI), 255-263, Springer, LNCS, 2016. Note: Acceptance rate: ~30%
Sebastiano Ferraris, Marco Lorenzi, Pankaj Daga, Marc Modat, Tom Vercauteren. Accurate small deformation exponential approximant to integrate large velocity fields: Application to image registration. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 17-24, 2016.
Marco Lorenzi, Boris A. Gutman, Derrek P. Hibar, Andre Altmann, Neda Jahanshad, Paul M. Thompson and Sebastien Ourselin. Partial Least Squares Modelling for Imaging genetics in Alzheimer's Disease: Plausibility and Generalization. IEEE International Symposium on Biomedical Imaging (ISBI), 2016.
Marco Lorenzi, Gabriel Ziegler, John Ashburner, Daniel Alexander and Sebastien Ourselin. Efficient Gaussian process Based Model of Spatio-Temporal Changes in Time Series of Images. Information Processing in Medical Imaging (IPMI), 24:626-37, Springer, LNCS, 2015. Note: Acceptance rate: ~30%
Marco Lorenzi , Gabriel Ziegler, Daniel C. Alexander, and Sebastien Ourselin. Modelling Non-Stationary and Non-Separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution, 1st ICML Workshop on Machine Learning Meets Medical Imaging. 9487, Springer, LNCS, 2015. Note: Oral podium presentation.
Boris A. Gutman, Tom P. Fletcher, Jorge M. Cardoso, Greig M. Fleishman, Marco Lorenzi, Paul M. Thompson, Sebastien Ourselin. A Riemannian Framework for Intrinsic Comparison of Closed Genus-Zero Shapes. Information Processing in Medical Imaging (IPMI), 24:205-18, Springer, LNCS, 2015. Note: Oral podium presentation. Acceptance rate: ~30%
Bishesh Khanal, Marco Lorenzi, Nicholas Ayache and Xavier Pennec. A biophysical model of shape changes due to atrophy in the brain with Alzheimer's disease . Medical Image Computing and Computer Aided Intervention (MICCAI), 17:41-8, Springer, LNCS, 2015. Note: Acceptance rate: ~30%
Marco Lorenzi, Bjoern Menze, H., Marc Niethammer, Nicholas Ayache, and Xavier Pennec. Sparse Scale-Space Decomposition of Volume Changes in Deformations Fields . Medical Image Computing and Computer Aided Intervention (MICCAI), 328-335, Springer, LNCS, 2013. Note: Acceptance rate: ~30%
Marco Lorenzi and Xavier Pennec. Parallel Transport with Pole Ladder: Application to Deformations of time Series of Images. In GSI2013 - Geometric Science of Information, Springer, LNCS, 8085, 68-75, 2013. Note: Oral podium presentation
Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Regional flux analysis of longitudinal atrophy in Alzheimer's disease. In Medical Image Computing and Computer Aided Intervention (MICCAI), 7510:739-746, Springer, LNCS, 2012. Note: Oral podium presentation. Acceptance rate: ~30%.
Marco Lorenzi, Giovanni B. Frisoni, Nicholas Ayache, and Xavier Pennec. Probabilistic Flux Analysis of Cerebral Longitudinal Atrophy. In MICCAI workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders (NIBAD 12), 256-265, 2012. Note: Oral podium presentation.
Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and Xavier Pennec. Mapping the effects of Aß142 levels on the longitudinal changes in healthy aging: hierarchical modeling based on stationary velocity fields. In Medical Image Computing and Computer Aided Intervention (MICCAI), 6892: 663-670, Springer, LNCS, 2011. Note: Acceptance rate: ~30%.
Marco Lorenzi, Nicholas Ayache, and Xavier Pennec. Schild's Ladder for the parallel transport of deformations in time series of images. Information Processing in Medical Imaging (IPMI), 6801: 463-474, Springer, LNCS, 2011. Note: Honorable Mention (runner-up) for the Erbsmann Award. Oral podium presentation, acceptance Rate: ~30%
Marco Lorenzi and Xavier Pennec. Geodesics, parallel transport & one-parameter subgroups. In 3rd MICCAI workshop on Mathematical Foundations of Computational Anatomy Workshop, September 2011. Note: Oral podium presentation
Marco Lorenzi, Nicholas Ayache, Giovanni B. Frisoni, and Xavier Pennec. 4D registration of serial brain MRIs images: a robust measure of changes applied to Alzheimer's disease. In MICCAI Workshop on Spatio- Temporal Image Analysis for Longitudinal and Time-Series Image Data, 2010. Note: Oral Podium Presentation, best presentation award
Book chapters
Xavier Pennec, Marco Lorenzi. Beyond Riemannian geometry: The affine connection setting for transformation groups. Riemannian Geometric Statistics in Medical Image Analysis, Elsevier, pp.169–229, 2020, 978–0–12–814725–2.
Marco Lorenzi and Xavier Pennec. Discrete Ladders for Parallel Transport in Transformation Groups with an Affine Connection Structure. Geometric Theory of Information Signals and Communication Technology, 243-271, Springer, 2014.
Oral Podium Presentation in Clinical Conferences
Marco Lorenzi, Helene Barelli. Blood Levels of Omega 3 and 6 across the Progression of Alzheimer's Disease. In Alzheimer's Association International Conference, Chicago, US, 2018.
Marco Lorenzi, Maurizio Filippone, Daniel C Alexander, Sebastien Ourselin. Modeling and prediction of the natural history of neurodegeneration from longitudinal trial data. In Alzheimer's Association International Conference, London, UK, 2017.
Marco Lorenzi, Boris A Gutman, Andre Altmann, Derrek P Hibar, Neda Jahanshad, Daniel C Alexander, Paul M Thompson, Sebastien Ourselin. Linking gene pathways and brain atrophy in Alzheimer's disease. In Alzheimer's Association International Conference, Toronto, CA, 2016. Note: Travel Fellowship Award
Marco Lorenzi , Nicholas Ayache, and Xavier Pennec, Giovanni B. Frisoni. Regional flux analysis of longitudinal atrophy in Alzheimer's disease. In Alzheimer's Association International Conference, Copenhagen, DK, 2014. Note: Travel Fellowship Award
Marco Lorenzi, Nicholas Ayache, Xavier Pennec, Giovanni B. Frisoni. Disentangling the normal aging from the pathological Alzheimer's disease progression on cross-sectional structural MR images. International Conference on Clinical Trials on Alzheimer's Disease (CTAD), Monte Carlo, Monaco, 2012.
Marco Lorenzi, Michael Donohue, Donata Paternic, Cristina Scarpazza, Susan Ostrowitzki, Olivier Blin, Elain Irving, Giovanni B. Frisoni. Enrichment through biomarkers in clinical trials of Alzheimer's drugs in patients with mild cognitive impairment. International Conference on Clinical Trials on Alzheimer's Disease (CTAD), Toulouse, France, 2010.
International Clinical Conference Abstracts
Marco Lorenzi, Ivor J. Simpson, Alex F. Mendelson, Sjoerd B. Vos, M. Jorge Cardoso, Marc Modat, Jonathan Schott, Sebastien Ourselin. Multimodal Image Analysis in Alzheimer's Disease via Statistical Modelling of Non-local Intensity Correlations . In Alzheimer's Association International Conference, Washington DC, USA, 2015.
Marco Lorenzi, Martina Bocchetta, Nicholas Ayache, Xavier Pennec, and Giovanni B. Frisoni. Conversion to MCI in healthy individuals with abnormal CSF Aß142 levels is associated with specific longitudinal morphological changes. In Alzheimer's Association International Conference, Boston, USA, 2013. Note: Travel Fellowship Award
Preprints
Yann Fraboni; Richard Vidal; Laetitia Kameni; Marco Lorenzi; On The Impact of Client Sampling on Federated Learning Convergence, 2019, arXiv preprint arXiv:2107.12211