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Publications of year 2019

Books and proceedings

  1. Dajiang Zhu, Jingwen Yan, Mads Nielsen, Tom Fletcher, Stanley Durrleman, Stefan Sommer, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, and Sarang Joshi, editors. Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy, volume 11846 of Lecture Notes in Computer Science (LNCS), October 2019. Springer. Keyword(s): Biomedical imaging, Artificial intelligence, Approximation methods, Statistics of surfaces, Statistical models, Principal component analysis, Neural networks, Machine learning, Imaging genetics, Image segmentation, Image registration, Image reconstruction, Image processing, Computational anatomy, Image fusion. [bibtex-entry]


Thesis

  1. Shuman Jia. Population-Based Models of Shape, Structure, and Deformation in Atrial Fibrillation. Theses, Université Côte d'Azur, December 2019. Keyword(s): cardiac image analysis, atrial fibrillation, segmentation, fat, statistical shape analysis, parallel transport, analyse d'images cardiaques, fibrillation auriculaire, segmentation, graisse, analyse statistique des formes, transport parallèle. [bibtex-entry]


  2. Pawel Mlynarski. Deep learning for segmentation of brain tumors and organs at risk in radiotherapy planning. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2019. Keyword(s): Convolutional Neural Networks, Semi-supervised learning, MRI, Radiotherapy, Brain tumor, Organs at risk, Réseau neuronal convolutif, Apprentissage semi-supervisé, IRM, Radiothérapie, Tumeur cérébrale, Organes à risque. [bibtex-entry]


  3. Raphaël Sivera. Modeling and measuring the brain morphological evolution using structural MRI in the context of neurodegenerative diseases. Theses, COMUE Université Côte d'Azur (2015 - 2019), November 2019. Keyword(s): Morphometry, Aging, Alzheimer's disease, MRI, Longitudinal models, Multivariate statistical analysis, Morphométrie, Vieillissement, Maladie d'Alzheimer, IRM, Modèles longitudinaux, Statistiques multivariées. [bibtex-entry]


  4. Qiao Zheng. Deep learning for robust segmentation and explainable analysis of 3d and dynamic cardiac images. Theses, COMUE Université Côte d'Azur (2015 - 2019), March 2019. Keyword(s): Deep learning, Cardiac segmentation, Cardiac analysis, Cine MRI, Apprentissage profond, Segmentation cardiaque, Analyse cardiaque, Ciné-IRM. [bibtex-entry]


Articles in journal, book chapters

  1. Clement Abi Nader, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data. NeuroImage, 2019. Keyword(s): Gaussian Process, Disease progression modeling, Alzheimer's disease, Bayesian modeling, Stochastic variational inference, Clinical trials. [bibtex-entry]


  2. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. Proceedings of Machine Learning Research, (97):302-311, 2019. [bibtex-entry]


  3. Nicholas Ayache and Sara Colantonio. The Digital Health Revolution - Introduction to the Special Theme. ERCIM News, (118):4-5, July 2019. [bibtex-entry]


  4. Laurent Bergé, Charles Bouveyron, Marco Corneli, and Pierre Latouche. The Latent Topic Block Model for the Co-Clustering of Textual Interaction Data. Computational Statistics and Data Analysis, 137:247-270, 2019. [bibtex-entry]


  5. Paloma Compes, Emeline Tabouret, Amandine Etcheverry, Carole Colin, Romain Appay, Nicolas Cordier, Jean Mosser, Olivier Chinot, Hervé Delingette, Nadine Girard, Henry Dufour, Philippe Metellus, and Dominique Figarella-Branger. Neuro-radiological characteristics of adult diffuse grade II and III insular gliomas classified according to WHO 2016. Journal of Neuro-Oncology, 142(3):511-520, 2019. Keyword(s): Molecular, Neuro-radiology, Insula, Glioma, Perfusion. [bibtex-entry]


  6. Claire Cury, Stanley Durrleman, David Cash, Marco Lorenzi, Jennifer M Nicholas, Martina Bocchetta, John C. Van Swieten, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, James Rowe, Caroline Graff, Fabrizio Tagliavini, Giovanni B. Frisoni, Robert Laforce, Elizabeth Finger, Alexandre de Mendonça, Sandro Sorbi, Sébastien Ourselin, Jonathan Rohrer, Marc Modat, Christin Andersson, Silvana Archetti, Andrea Arighi, Luisa Benussi, Sandra Black, Maura Cosseddu, Marie Fallstrm, Carlos G. Ferreira, Chiara Fenoglio, Nick Fox, Morris Freedman, Giorgio Fumagalli, Stefano Gazzina, Robert Ghidoni, Marina Grisoli, Vesna Jelic, Lize Jiskoot, Ron Keren, Gemma Lombardi, Carolina Maruta, Lieke Meeter, Rick van Minkelen, Benedetta Nacmias, Linn Ijerstedt, Alessandro Padovani, Jessica Panman, Michela Pievani, Cristina Polito, Enrico Premi, Sara Prioni, Rosa Rademakers, Veronica Redaelli, Ekaterina Rogaeva, Giacomina Rossi, Martin Rossor, Elio Scarpini, David Tang-Wai, Hakan Thonberg, Pietro Tiraboschi, Ana Verdelho, and Jason Warren. Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort. NeuroImage, 188:282-290, March 2019. Keyword(s): Spatiotemporal geodesic regression, Parallel transport, Shape analysis, Clustering, Computational anatomy, Thalamus. [bibtex-entry]


  7. Thomas Demarcy, Isabelle Pélisson, Dan Gnansia, Hervé Delingette, Nicholas Ayache, Charles Raffaelli, Clair Vandersteen, and Nicolas Guevara. Un modèle de reconstruction tridimensionnelle de la cochlée au service de l'implantation cochléaire. Les cahiers de l'audition, 32(4):36-40, July 2019. [bibtex-entry]


  8. Rubén Doste, David Soto-Iglesias, Gabriel Bernardino, Alejandro Alcaine, Rafael Sebastian, Sophie Giffard-Roisin, Maxime Sermesant, Antonio Berruezo, Damian Sanchez-Quintana, and Oscar Camara. A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts. International Journal for Numerical Methods in Biomedical Engineering, 35(4), March 2019. Keyword(s): Rule-based method, Fiber orientation, Outflow tract, Septum, Electrophysiological simulations, Outflow tract ventricular arrhythmia. [bibtex-entry]


  9. Simon Heeke, Jonathan Benzaquen, Elodie Long-Mira, Benoît Audelan, Virginie Lespinet, Olivier Bordone, Salomé Lalvée, Katia Zahaf, Michel Poudenx, Olivier Humbert, Henri Montaudié, Pierre-Michel Dugourd, Madleen Chassang, Thierry Passeron, Hervé Delingette, Charles-Hugo Marquette, Véronique Hofman, Albrecht Stenzinger, Marius Ilié, and Paul Hofman. In-House Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-Small Cell Lung Cancer and Melanoma Patients. Cancers, 11, 2019. Keyword(s): lung cancer, melanoma, immunotherapy, tumor mutational burden, FoundationOne assay, Oncomine TML assay. [bibtex-entry]


  10. Simon Heeke, Hervé Delingette, Youta Fanjat, Elodie Long-Mira, Sandra Lassalle, Véronique Hofman, Jonathan Benzaquen, Charles-Hugo Marquette, Paul Hofman, and Marius Ilié. La pathologie cancéreuse pulmonaire à l'heure de l'intelligence artificielle : entre espoir, désespoir et perspectives. Annales de Pathologie, 39(2):130-136, April 2019. Keyword(s): Pathology, Histology, Lung cancer, Artificial intelligence, Convolutional neural networks, Deep learning, Pathologie Apprentissage profond, Histologie, Cancer broncho-pulmonair, Intelligence artificielle, Réseaux de neurones convolutifs, Apprentissage profond. [bibtex-entry]


  11. Paul Hofman, Nicholas Ayache, Pascal Barbry, Michel Barlaud, Audrey Bel, Philippe Blancou, Frédéric Checler, Sylvie Chevillard, Gael Cristofari, Mathilde Demory, Vincent Esnault, Claire Falandry, Eric Gilson, Olivier Guerin, Nicolas Glaichenhaus, Joël Guigay, Marius I. Ilie, Bernard Mari, Charles-Hugo Marquette, Véronique Paquis-Flucklinger, Frédéric Prate, Pierre Saintigny, Barbara Seitz-Polsky, Taycir Skhiri, Ellen Van Obberghen-Schilling, Emmanuel Van Obberghen, and Laurent Yvan-Charvet. The OncoAge Consortium: Linking Aging and Oncology from Bench to Bedside and Back Again. Cancers, 11(2):1-11, February 2019. Keyword(s): aging, education, research, optimization, well-being, cancer, elderly. [bibtex-entry]


  12. Julian Krebs, Hervé Delingette, Boris Mailhé, Nicholas Ayache, and Tommaso Mansi. Learning a Probabilistic Model for Diffeomorphic Registration. IEEE Transactions on Medical Imaging, pp 2165-2176, February 2019. Keyword(s): deep learning, probabilistic encoding, conditional variational autoencoder, latent variable model, deformation transport, deformable registration. [bibtex-entry]


  13. Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. 3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context. Computerized Medical Imaging and Graphics, 73:60-72, February 2019. Keyword(s): Brain tumor, Multisequence MRI, Ensembles of models, Segmentation, 3D Convolutional Neural Networks. [bibtex-entry]


  14. Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, and Nicholas Ayache. Deep Learning with Mixed Supervision for Brain Tumor Segmentation. Journal of Medical Imaging, July 2019. Keyword(s): Convolutional Neural Networks, Semi-supervised learning, segmentation, tumor, MRI, Semi-supervised..., Convolutional N.... [bibtex-entry]


  15. Roch Molléro, Xavier Pennec, Hervé Delingette, Nicholas Ayache, and Maxime Sermesant. Population-based priors in cardiac model personalisation for consistent parameter estimation in heterogeneous databases. International Journal for Numerical Methods in Biomedical Engineering, 35(2):e3158, February 2019. Keyword(s): Parameter Selection, Personalised modeling, Parameter Estimation, Cardiac Electromechanical Modeling. [bibtex-entry]


  16. Fanny Orlhac, Charles Bouveyron, and Nicholas Ayache. Radiomics: How to Make Medical Images Speak?. ERCIM News, (118):7-8, July 2019. [bibtex-entry]


  17. Fanny Orlhac, Frédérique Frouin, Christophe Nioche, Nicholas Ayache, and Irène Buvat. Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics. Radiology, 291(1):53-59, April 2019. [bibtex-entry]


  18. Maxime Sermesant. Improving Cardiac Arrhythmia Therapy with Medical Imaging. ERCIM News, (118):10-11, July 2019. [bibtex-entry]


  19. Raphaël Sivera, Hervé Delingette, Marco Lorenzi, Xavier Pennec, and Nicholas Ayache. A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments. NeuroImage, 198:255-270, September 2019. Keyword(s): Deformations, Aging, Alzheimer's disease, Imaging biomarkers, Spatio-temporal model, Brain morphology. [bibtex-entry]


  20. Masateru Takigawa, Josselin Duchateau, Frederic Sacher, Ruairidh Martin, Konstantinos Vlachos, Takeshi Kitamura, Maxime Sermesant, Nicolas Cedilnik, Ghassen Cheniti, Antonio Frontera, Nathaniel Thompson, Calire Martin, Grégoire Massoullié, Felix Bourier, Anna Lam, Michael Wolf, William Escande, Clémentine André, Thomas Pambrun, Arnaud Denis, Nicolas Derval, Mélèze Hocini, Michel Haïssaguerre, Hubert Cochet, and Pierre Jaïs. Are wall thickness channels defined by computed tomography predictive of isthmuses of postinfarction ventricular tachycardia?. Heart Rhythm, 16(11):1661-1668, June 2019. Keyword(s): Isthmus, High-resolution mapping, Contrart-enhanced multidetector computed tomography, MUSIC, Myocardial infarction, Ventricular tachycardia, Wall thickness. [bibtex-entry]


  21. Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Nicholas Ayache, Bruno Stankoff, and Olivier Colliot. Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis. Medical Image Analysis, 58(101546), December 2019. Keyword(s): Adversarial Training, Multiple Sclerosis, PET Imaging, Multimodal MRI. [bibtex-entry]


  22. Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Olivier Colliot, Bruno Stankoff, and Nicholas Ayache. Fluid-attenuated inversion recovery MRI synthesis from multisequence MRI using three-dimensional fully convolutional networks for multiple sclerosis. Journal of Medical Imaging, 6(01), February 2019. Keyword(s): MR Images, FLAIR Synthesis, 3D Fully Convolutional Networks, Multiple Sclerosis, Deep Learning. [bibtex-entry]


  23. Wilhelm Wimmer, Lukas Anschuetz, Stefan Weder, Franca Wagner, Hervé Delingette, and Marco Caversaccio. Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks. Data in Brief, 27:104782, December 2019. Keyword(s): Vestibule, Semicircular canals, Morphology, Anatomy, Cochlea, Inner ear. [bibtex-entry]


  24. Qiao Zheng, Hervé Delingette, and Nicholas Ayache. Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow. Medical Image Analysis, 56:80-95, 2019. Keyword(s): Classifi-cation, Motion, Cine MRI, Deep learn- ing, Semi-supervised learning, Neural network, Cardiac pathology, Classifi- cation, Apparent flow, Deep learn-ing. [bibtex-entry]


Conference articles

  1. Luigi Antelmi, Nicholas Ayache, Philippe Robert, and Marco Lorenzi. Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data. In ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, June 2019. [bibtex-entry]


  2. Benoît Audelan and Hervé Delingette. Unsupervised Quality Control of Image Segmentation based on Bayesian Learning. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, October 2019. Keyword(s): Bayesian learning, Image segmentation, Quality control. [bibtex-entry]


  3. Nicholas Ayache. AI and Healthcare: towards a Digital Twin?. In MCA 2019 - 5th International Symposium on Multidiscplinary Computational Anatomy, Fukuoka, Japan, March 2019. [bibtex-entry]


  4. Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, and Maxime Sermesant. EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions. In FIMH 2019 - 10th International Conference on Functional Imaging of the Hearth, Bordeaux, France, pages 55-63, June 2019. Springer. [bibtex-entry]


  5. Tania Bacoyannis, Julian Krebs, Nicolas Cedilnik, Hubert Cochet, and Maxime Sermesant. Deep Learning Formulation of ECGI for Data-driven Integration of Spatiotemporal Correlations and Imaging Information. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, volume LNCS 11504, Bordeaux, France, pages 20-28, June 2019. Springer. Keyword(s): Simulation, Generative Model, Deep learning, ECGI. [bibtex-entry]


  6. Jaume Banus, Marco Lorenzi, Oscar Camara, and Maxime Sermesant. Large Scale Cardiovascular Model Personalisation for Mechanistic Analysis of Heart and Brain Interactions. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, Bordeaux, France, pages 285-293, June 2019. [bibtex-entry]


  7. Nicolas Cedilnik, Josselin Duchateau, Frederic Sacher, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Fully Automated Electrophysiological Model Personalisation Framework from CT Imaging. In FIMH 2019 - 10th International Conference on Functional Imaging and Modeling of the Heart, Bordeaux, France, pages 325-333, June 2019. Keyword(s): Model Personalisation, Deep learning, Segmentation, Imaging. [bibtex-entry]


  8. Nicolas Cedilnik, Shuman Jia, Pierre Jaïs, Hubert Cochet, and Maxime Sermesant. Automatic non-invasive substrate analysis from CT images in post-infarction VT. In EHRA 2019 - European Heart Rhythm Association, volume 21, Lisbonne, Portugal, pages 720-739, March 2019. [bibtex-entry]


  9. Nicolas Cedilnik and Maxime Sermesant. Eikonal Model Personalisation using Invasive Data to Predict Cardiac Resynchronisation Therapy Electrophysiological Response. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzen, China, October 2019. Keyword(s): Cardiac resynchronisation therapy, Electrophysiology, Computer model, Personalisation. [bibtex-entry]


  10. Gaëtan Desrues, Hervé Delingette, and Maxime Sermesant. Towards Hyper-Reduction of Cardiac Models using Poly-Affine Deformation. In STACOM 2019: Statistical Atlases and Computational Models of the Heart, Shenzhen, China, October 2019. [bibtex-entry]


  11. Sara Garbarino and Marco Lorenzi. Modeling and inference of spatio-temporal protein dynamics across brain networks. In International Conference on Information Processing in Medical Imaging, volume 11492 of Lecture Notes in Computer Science book series, Hong Kong, Hong Kong SAR China, pages 57-69, June 2019. springer. Note: Bayesian non--parametric model, protein propagation, Alzheimer'sdisease, Gaussian process, dynamical systems, spatio--temporal model, disease progression modeling. [bibtex-entry]


  12. Nicolas Guigui, Shuman Jia, Maxime Sermesant, and Xavier Pennec. Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 759-768, August 2019. F. Nielsen and F. Barbaresco, Springer. Keyword(s): Shape Registration, Parallel Transport, Symmetric Spaces. [bibtex-entry]


  13. Julian Krebs, Tommaso Mansi, Nicholas Ayache, and Hervé Delingette. Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Note: Probabilistic Motion Model, Motion Tracking, Temporal Super-Resolution, Diffeomorphic Registration, Temporal Variational Autoencoder. [bibtex-entry]


  14. Buntheng Ly, Hubert Cochet, and Maxime Sermesant. Style Data Augmentation for Robust Segmentation of Multi-Modality Cardiac MRI. In STACOM 2019 - 10th Workhop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Keyword(s): Late Gadolinium Enhanced, Multi-modality, Cardiac Magnetic Resonance Imaging, Image segmentation, Deep Learning. [bibtex-entry]


  15. Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Céline Sanfiorenzo, Fabien Squara, Emile Ferrari, and Maxime Sermesant. Incremental prognostic value of changes in 3D right ventricular function in pulmonary hypertension. In JE SFC 2019 - 29es Journées Européennes de la Société Française de Cardiologie, Paris, France, January 2019. [bibtex-entry]


  16. Pamela Moceri, Nicolas Duchateau, Delphine Baudouy, Fabien Squara, Emile Ferrari, and Maxime Sermesant. 3D right ventricular strain and shape in volume overload: comparative analysis of Tetralogy of Fallot and atrial septal defect patients. In JE SFC 2019 - 29es Journées Européennes de la Société Française de Cardiologie, Paris, France, January 2019. [bibtex-entry]


  17. Yann Thanwerdas and Xavier Pennec. Exploration of Balanced Metrics on Symmetric Positive Definite Matrices. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 484-493, August 2019. Springer. Keyword(s): Information geometry, SPD matrices, Dually flat connections. [bibtex-entry]


  18. Yann Thanwerdas and Xavier Pennec. Is affine invariance well defined on SPD matrices? A principled continuum of metrics. In GSI 2019 - 4th conference on Geometric Science of Information, volume Lecture Notes in Computer Science 11712 of Proceedings of Geometric Science of Information, Toulouse, France, pages 502-510, August 2019. Springer. Keyword(s): Riemannian symmetric spaces, SPD matrices. [bibtex-entry]


  19. Zihao Wang, Clair Vandersteen, Thomas Demarcy, Dan Gnansia, Charles Raffaelli, Nicolas Guevara, and Hervé Delingette. Deep Learning based Metal Artifacts Reduction in post-operative Cochlear Implant CT Imaging. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Shenzhen, China, pages 121-129, October 2019. Keyword(s): Metal Artifacts Reduction, Generative adversarial networks. [bibtex-entry]


  20. Wilhelm Wimmer, Clair Vandersteen, Nicolas Guevara, Marco Caversaccio, and Hervé Delingette. Robust Cochlear Modiolar Axis Detection in CT. In MICCAI 2019 - 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, Shenzhen, China, pages 3-10, October 2019. Keyword(s): Approximate maximum like-lihood, Natural growth, Kinematic surface recognition. [bibtex-entry]


  21. Yingyu Yang, Stephane Gillon, Jaume Banus, Pamela Moceri, and Maxime Sermesant. Non-Invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-driven or Model-based?. In STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Shenzhen, China, October 2019. Keyword(s): Cardiac modelling, Machine learning, Pulmonary hypertension. [bibtex-entry]


Patents, standards

  1. Julian Krebs, Hervé Delingette, Nicholas Ayache, Tommaso Mansi, and Shun Miao. Medical Imaging Diffeomorphic Registration based on Machine Learning. US 2019/0205766 A1, United States, July 2019. [bibtex-entry]


Miscellaneous

  1. Valeria Manera, Luigi Antelmi, Radia Zeghari, Nicholas Ayache, Marco Lorenzi, and Philippe Robert. Prevalence of lack of interest and anhedonia in the general population of the UK Biobank. AAIC 2019 - Alzheimer's Association International Conference, July 2019. Note: Poster. [bibtex-entry]


  2. Radia Zeghari, Philippe Robert, Valeria Manera, Marco Lorenzi, and Alexandra König. Towards a Multidimensional Assessment of Apathy in Neurocognitive Disorders. AAIC 2019 - Alzheimer's Association International Conference, July 2019. Note: Poster. [bibtex-entry]


  3. Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, and Xavier Pennec. geomstats: a Python Package for Riemannian Geometry in Machine Learning. Note: Preprint NIPS2018, January 2019. [bibtex-entry]


  4. Xavier Pennec. Curvature effects on the empirical mean in Riemannian and affine Manifolds: a non-asymptotic high concentration expansion in the small-sample regime. Note: Working paper or preprint, June 2019. Keyword(s): empirical mean, affine connection manifold, non-asymptotic estimation, Fréchet means, curvature, Riemannian manifold. [bibtex-entry]



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