-
Gaëtan Desrues.
Personalised 3D electromechanical models of the heart for cardiac resynchronisation therapy planning in heart failure patients.
Theses,
Université Côte d'Azur,
March 2023.
Keyword(s): Patient-specific simulation,
Digital twin,
ECG,
CRT,
Cardiac electrophysiology,
Biomechanics,
Finite element method,
Artificial intelligence,
Simulation personnalisée,
Jumeau numérique,
ECG,
CRT,
Électrophysiologie cardiaque,
Biomécanique,
Méthode des éléments finis,
Intelligence artificielle.
@phdthesis{desrues:tel-04220830,
TITLE = {{Personalised 3D electromechanical models of the heart for cardiac resynchronisation therapy planning in heart failure patients}},
AUTHOR = {Desrues, Ga{\"e}tan},
url-hal= {https://theses.hal.science/tel-04220830},
NUMBER = {2023COAZ4030},
SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
YEAR = {2023},
MONTH = Mar,
KEYWORDS = {Patient-specific simulation ; Digital twin ; ECG ; CRT ; Cardiac electrophysiology ; Biomechanics ; Finite element method ; Artificial intelligence ; Simulation personnalis{\'e}e ; Jumeau num{\'e}rique ; ECG ; CRT ; {\'E}lectrophysiologie cardiaque ; Biom{\'e}canique ; M{\'e}thode des {\'e}l{\'e}ments finis ; Intelligence artificielle},
TYPE = {Theses},
PDF = {https://theses.hal.science/tel-04220830/file/2023COAZ4030.pdf},
HAL_ID = {tel-04220830},
HAL_VERSION = {v1},
}
-
Yann Fraboni.
Reliability and robustness of federated learning in practical applications.
Theses,
Université Côte d'Azur,
May 2023.
Keyword(s): Federated learning,
Heterogeneous data,
Privacy,
Distributed optimization,
Bias,
Apprentissage fédéré,
Données hétérogènes,
Protection des données,
Optimisation distribuée,
Biais.
@phdthesis{fraboni:tel-04141520,
TITLE = {{Reliability and robustness of federated learning in practical applications}},
AUTHOR = {Fraboni, Yann},
url-hal= {https://theses.hal.science/tel-04141520},
NUMBER = {2023COAZ4033},
SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
YEAR = {2023},
MONTH = May,
KEYWORDS = {Federated learning ; Heterogeneous data ; Privacy ; Distributed optimization ; Bias ; Apprentissage f{\'e}d{\'e}r{\'e} ; Donn{\'e}es h{\'e}t{\'e}rog{\`e}nes ; Protection des donn{\'e}es ; Optimisation distribu{\'e}e ; Biais},
TYPE = {Theses},
PDF = {https://theses.hal.science/tel-04141520/file/2023COAZ4033.pdf},
HAL_ID = {tel-04141520},
HAL_VERSION = {v1},
}
-
Dimitri Hamzaoui.
AI-based diagnosis of prostate cancer from multiparametric MRI.
Theses,
Université Côte d'Azur,
June 2023.
Keyword(s): Machine learning,
Prostate-cancer,
Inter-expert variability,
Segmentation,
Consensus,
Medical imaging,
Artificial intelligence,
Apprentissage profond,
Prostate-cancer,
Variabilité inter-expert,
Segmentation,
Consensus,
Imagerie médicale,
Intelligence artificielle.
@phdthesis{hamzaoui:tel-04166332,
TITLE = {{AI-based diagnosis of prostate cancer from multiparametric MRI}},
AUTHOR = {Hamzaoui, Dimitri},
url-hal= {https://hal.science/tel-04166332},
NUMBER = {2023COAZ4044},
SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Machine learning ; Prostate-cancer ; Inter-expert variability ; Segmentation ; Consensus ; Medical imaging ; Artificial intelligence ; Apprentissage profond ; Prostate-cancer ; Variabilit{\'e} inter-expert ; Segmentation ; Consensus ; Imagerie m{\'e}dicale ; Intelligence artificielle},
TYPE = {Theses},
PDF = {https://hal.science/tel-04166332v2/file/2023COAZ4044.pdf},
HAL_ID = {tel-04166332},
HAL_VERSION = {v2},
}
-
Victoriya Kashtanova.
Learning cardiac electrophysiology dynamics with PDE-based physiological constraints for data-driven personalised predictions.
Theses,
Université Côte d'Azur,
June 2023.
Keyword(s): Physics-based learning,
Deep learning,
Cardiac electrophysiology,
Model personalisation,
PDE,
Simulations,
Apprentissage basé sur la physique,
Apprentissage profond,
Electrophysiologie cardiaque,
Personnalisation de modèle,
EDP,
Simulations.
@phdthesis{kashtanova:tel-04176798,
TITLE = {{Learning cardiac electrophysiology dynamics with PDE-based physiological constraints for data-driven personalised predictions}},
AUTHOR = {Kashtanova, Victoriya},
url-hal= {https://hal.science/tel-04176798},
NUMBER = {2023COAZ4043},
SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Physics-based learning ; Deep learning ; Cardiac electrophysiology ; Model personalisation ; PDE ; Simulations ; Apprentissage bas{\'e} sur la physique ; Apprentissage profond ; Electrophysiologie cardiaque ; Personnalisation de mod{\`e}le ; EDP ; Simulations},
TYPE = {Theses},
PDF = {https://hal.science/tel-04176798v2/file/2023COAZ4043.pdf},
HAL_ID = {tel-04176798},
HAL_VERSION = {v2},
}
-
Santiago Smith Silva Rincon.
Federated learning of biomedical data in multicentric imaging studies.
Theses,
Université Côte d'Azur,
July 2023.
Keyword(s): Federated learning,
Healthcare,
Data protection,
GDPR,
CCPA,
Medical imaging,
Data harmonization,
Meta-analyzis,
Mega-analyzis,
Fed-BioMed,
Bayesian optimization,
Radom effect models,
FedComBat,
Apprentissage fédéré,
Santé,
Protection des données,
RGPD,
CCPA,
Imageie médicale,
Harmonisation des données,
Méta-analyse,
Méganalyse,
Fed-BioMed,
Optimisation bayésienne,
Modèles à effets aléatoires,
FedComBat.
@phdthesis{silvarincon:tel-04249209,
TITLE = {{Federated learning of biomedical data in multicentric imaging studies}},
AUTHOR = {Silva Rincon, Santiago Smith},
url-hal= {https://theses.hal.science/tel-04249209},
NUMBER = {2023COAZ4056},
SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
YEAR = {2023},
MONTH = Jul,
KEYWORDS = {Federated learning ; Healthcare ; Data protection ; GDPR ; CCPA ; Medical imaging ; Data harmonization ; Meta-analyzis ; Mega-analyzis ; Fed-BioMed ; Bayesian optimization ; Radom effect models ; FedComBat ; Apprentissage f{\'e}d{\'e}r{\'e} ; Sant{\'e} ; Protection des donn{\'e}es ; RGPD ; CCPA ; Imageie m{\'e}dicale ; Harmonisation des donn{\'e}es ; M{\'e}ta-analyse ; M{\'e}ganalyse ; Fed-BioMed ; Optimisation bay{\'e}sienne ; Mod{\`e}les {\`a} effets al{\'e}atoires ; FedComBat},
TYPE = {Theses},
PDF = {https://theses.hal.science/tel-04249209/file/2023COAZ4056.pdf},
HAL_ID = {tel-04249209},
HAL_VERSION = {v1},
}
-
Paul Tourniaire.
AI-based selection of imaging and biological markers predictive of therapy response in lung cancer.
Theses,
Université Côte d'Azur,
June 2023.
Keyword(s): Digital pathology,
Multiple instance learning,
Mixed supervision,
Deep learning,
Survival analysis,
Lung cancer,
Immunotherapy,
Histopathologie numérique,
Apprentissage multi-instance,
Supervision mélangée,
Apprentissage profond,
Analyse de survie,
Cancer du poumon,
Immunothérapie.
@phdthesis{tourniaire:tel-04189450,
TITLE = {{AI-based selection of imaging and biological markers predictive of therapy response in lung cancer}},
AUTHOR = {Tourniaire, Paul},
url-hal= {https://theses.hal.science/tel-04189450},
NUMBER = {2023COAZ4041},
SCHOOL = {{Universit{\'e} C{\^o}te d'Azur}},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Digital pathology ; Multiple instance learning ; Mixed supervision ; Deep learning ; Survival analysis ; Lung cancer ; Immunotherapy ; Histopathologie num{\'e}rique ; Apprentissage multi-instance ; Supervision m{\'e}lang{\'e}e ; Apprentissage profond ; Analyse de survie ; Cancer du poumon ; Immunoth{\'e}rapie},
TYPE = {Theses},
PDF = {https://theses.hal.science/tel-04189450v2/file/2023COAZ4041.pdf},
HAL_ID = {tel-04189450},
HAL_VERSION = {v2},
}
-
Arnaud Berenbaum,
Hervé Delingette,
Aurélien Maire,
Cécile Poret,
Claire Hassen-Khodja,
Stéphane Bréant,
Christel Daniel,
Patricia Martel,
Lamiae Grimaldi,
Marie Frank,
Emmanuel Durand,
and Florent Besson.
Performance of AI-Based Automated Classifications of Whole-Body FDG PET in Clinical Practice: The CLARITI Project.
Applied Sciences,
13(9):5281,
May 2023.
Keyword(s): FDG PET,
artificial intelligence,
deep learning,
convolutional neural network.
@article{berenbaum:hal-04081046,
TITLE = {{Performance of AI-Based Automated Classifications of Whole-Body FDG PET in Clinical Practice: The CLARITI Project}},
AUTHOR = {Berenbaum, Arnaud and Delingette, Herv{\'e} and Maire, Aur{\'e}lien and Poret, C{\'e}cile and Hassen-Khodja, Claire and Br{\'e}ant, St{\'e}phane and Daniel, Christel and Martel, Patricia and Grimaldi, Lamiae and Frank, Marie and Durand, Emmanuel and Besson, Florent},
url-hal= {https://inria.hal.science/hal-04081046},
JOURNAL = {{Applied Sciences}},
PUBLISHER = {{Multidisciplinary digital publishing institute (MDPI)}},
VOLUME = {13},
NUMBER = {9},
PAGES = {5281},
YEAR = {2023},
MONTH = May,
DOI = {10.3390/app13095281},
KEYWORDS = {FDG PET ; artificial intelligence ; deep learning ; convolutional neural network},
HAL_ID = {hal-04081046},
HAL_VERSION = {v1},
}
-
Nina Brillat-Savarin,
Carine Wu,
Laurène Aupin,
Camille Thoumin,
Dimitri Hamzaoui,
and Raphaële Renard-Penna.
3.0 T prostate MRI: Visual assessment of 2D and 3D T2-weighted imaging sequences using PI-QUAL score.
European Journal of Radiology,
166:110974,
September 2023.
@article{brillatsavarin:hal-04162794,
TITLE = {{3.0 T prostate MRI: Visual assessment of 2D and 3D T2-weighted imaging sequences using PI-QUAL score}},
AUTHOR = {Brillat-Savarin, Nina and Wu, Carine and Aupin, Laur{\`e}ne and Thoumin, Camille and Hamzaoui, Dimitri and Renard-Penna, Rapha{\"e}le},
url-hal= {https://hal.science/hal-04162794},
JOURNAL = {{European Journal of Radiology}},
PUBLISHER = {{Elsevier}},
VOLUME = {166},
PAGES = {110974},
YEAR = {2023},
MONTH = Sep,
DOI = {10.1016/j.ejrad.2023.110974},
HAL_ID = {hal-04162794},
HAL_VERSION = {v1},
}
-
Nicolas Cedilnik,
Mihaela Pop,
Josselin Duchateau,
Frédéric Sacher,
Pierre Jaïs,
Hubert Cochet,
and Maxime Sermesant.
Efficient Patient-Specific Simulations of Ventricular Tachycardia Based on Computed Tomography-Defined Wall Thickness Heterogeneity.
JACC: Clinical Electrophysiology,
September 2023.
Keyword(s): Cardiac modeling,
Electrophysiology modeling,
CT,
Ventricular tachycardia,
Medical simulation.
@article{cedilnik:hal-04255556,
TITLE = {{Efficient Patient-Specific Simulations of Ventricular Tachycardia Based on Computed Tomography-Defined Wall Thickness Heterogeneity}},
AUTHOR = {Cedilnik, Nicolas and Pop, Mihaela and Duchateau, Josselin and Sacher, Fr{\'e}d{\'e}ric and Ja{\"i}s, Pierre and Cochet, Hubert and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-04255556},
JOURNAL = {{JACC: Clinical Electrophysiology}},
PUBLISHER = {{Elsevier}},
YEAR = {2023},
MONTH = Sep,
DOI = {10.1016/j.jacep.2023.08.008},
KEYWORDS = {Cardiac modeling ; Electrophysiology modeling ; CT ; Ventricular tachycardia ; Medical simulation},
PDF = {https://inria.hal.science/hal-04255556/file/cedilnik-jaccep-2023.pdf},
HAL_ID = {hal-04255556},
HAL_VERSION = {v1},
}
-
Quentin Clairon,
Chloé Pasin,
Irene Balelli,
Rodolphe Thiébaut,
and Mélanie Prague.
Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: An optimal control approach.
Computational Statistics,
September 2023.
Keyword(s): Dynamic population models,
Ordinary differential equations,
Optimal control theory,
Mechanistic models,
Nonlinear mixed effects models,
Clinical trial analysis.
@article{clairon:hal-03335826,
TITLE = {{Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: An optimal control approach}},
AUTHOR = {Clairon, Quentin and Pasin, Chlo{\'e} and Balelli, Irene and Thi{\'e}baut, Rodolphe and Prague, M{\'e}lanie},
url-hal= {https://hal.science/hal-03335826},
JOURNAL = {{Computational Statistics}},
PUBLISHER = {{Springer Verlag}},
YEAR = {2023},
MONTH = Sep,
KEYWORDS = {Dynamic population models ; Ordinary differential equations ; Optimal control theory ; Mechanistic models ; Nonlinear mixed effects models ; Clinical trial analysis},
PDF = {https://hal.science/hal-03335826v2/file/Manuscript_Estimation_NLMEODE_via_OCA_CompStat%20%281%29.pdf},
HAL_ID = {hal-03335826},
HAL_VERSION = {v2},
}
-
Hind Dadoun,
Hervé Delingette,
Anne-Laure Rousseau,
Eric de Kerviler,
and Nicholas Ayache.
Deep Clustering for Abdominal Organ Classification in US imaging.
Journal of Medical Imaging,
10(3):034502,
2023.
Keyword(s): ultrasound imaging,
representation learning,
deep clustering,
semi-supervised learning.
@article{dadoun:hal-03773082,
TITLE = {{Deep Clustering for Abdominal Organ Classification in US imaging}},
AUTHOR = {Dadoun, Hind and Delingette, Herv{\'e} and Rousseau, Anne-Laure and de Kerviler, Eric and Ayache, Nicholas},
url-hal= {https://inria.hal.science/hal-03773082},
JOURNAL = {{Journal of Medical Imaging}},
PUBLISHER = {{SPIE Digital Library}},
VOLUME = {10},
NUMBER = {3},
PAGES = {034502},
YEAR = {2023},
DOI = {10.1117/1.JMI.10.3.034502},
KEYWORDS = {ultrasound imaging ; representation learning ; deep clustering ; semi-supervised learning},
PDF = {https://inria.hal.science/hal-03773082v3/file/soumission_jmi_dadoun_vf.pdf},
HAL_ID = {hal-03773082},
HAL_VERSION = {v3},
}
-
Nicolas Guigui,
Nina Miolane,
and Xavier Pennec.
Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats.
Foundations and Trends in Machine Learning,
16(3):329-493,
February 2023.
Keyword(s): Riemannian Geometry,
Geometric Statistics,
Python Library.
@article{guigui:hal-03766900,
TITLE = {{Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats}},
AUTHOR = {Guigui, Nicolas and Miolane, Nina and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-03766900},
JOURNAL = {{Foundations and Trends in Machine Learning}},
PUBLISHER = {{Now Publishers}},
VOLUME = {16},
NUMBER = {3},
PAGES = {329-493},
YEAR = {2023},
MONTH = Feb,
DOI = {10.1561/2200000098},
KEYWORDS = {Riemannian Geometry ; Geometric Statistics ; Python Library},
PDF = {https://inria.hal.science/hal-03766900v2/file/main-now.pdf},
HAL_ID = {hal-03766900},
HAL_VERSION = {v2},
}
-
Dimitri Hamzaoui,
Sarah Montagne,
Raphaële Renard-Penna,
Nicholas Ayache,
and Hervé Delingette.
Morphologically-Aware Consensus Computation via Heuristics-based IterATive Optimization (MACCHIatO).
Journal of Machine Learning for Biomedical Imaging,
2(UNSURE 2022 Special Issue):361-389,
September 2023.
Keyword(s): Consensus,
Distance,
Heuristic,
Optimization,
STAPLE.
@article{hamzaoui:hal-04208018,
TITLE = {{Morphologically-Aware Consensus Computation via Heuristics-based IterATive Optimization (MACCHIatO)}},
AUTHOR = {Hamzaoui, Dimitri and Montagne, Sarah and Renard-Penna, Rapha{\"e}le and Ayache, Nicholas and Delingette, Herv{\'e}},
url-hal= {https://hal.science/hal-04208018},
JOURNAL = {{Journal of Machine Learning for Biomedical Imaging}},
PUBLISHER = {{Melba editors}},
VOLUME = {2},
NUMBER = {UNSURE 2022 Special Issue},
PAGES = {361-389},
YEAR = {2023},
MONTH = Sep,
DOI = {10.59275/j.melba.2023-219c},
KEYWORDS = {Consensus ; Distance ; Heuristic ; Optimization ; STAPLE},
PDF = {https://hal.science/hal-04208018/file/MOJITO_MELBA.pdf},
HAL_ID = {hal-04208018},
HAL_VERSION = {v1},
}
-
Philipp Harms,
Peter W. Michor,
Xavier Pennec,
and Stefan Sommer.
Geometry of Sample Spaces.
Differential Geometry and its Applications,
90:102029,
October 2023.
Note: 29 pages, 1 figure.
@article{harms:hal-02972385,
TITLE = {{Geometry of Sample Spaces}},
AUTHOR = {Harms, Philipp and Michor, Peter W. and Pennec, Xavier and Sommer, Stefan},
url-hal= {https://inria.hal.science/hal-02972385},
NOTE = {29 pages, 1 figure},
JOURNAL = {{Differential Geometry and its Applications}},
PUBLISHER = {{Elsevier}},
VOLUME = {90},
PAGES = {102029},
YEAR = {2023},
MONTH = Oct,
DOI = {10.1016/j.difgeo.2023.102029},
HAL_ID = {hal-02972385},
HAL_VERSION = {v1},
}
-
Sébastien Molière,
Dimitri Hamzaoui,
Anna Luzurier,
Benjamin Granger,
Sarah Montagne,
Alexandre Allera,
Malek Ezziane,
Raphaële Quint,
Mehdi Kalai,
Nicholas Ayache,
Hervé Delingette,
and Raphaële Renard-Penna.
Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI.
Diagnostic and Interventional Imaging,
August 2023.
Keyword(s): Artificial intelligence Inter-reader variability Magnetic resonance imaging Prostate Segmentation.
@article{moliere:hal-04185065,
TITLE = {{Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI}},
AUTHOR = {Moli{\`e}re, S{\'e}bastien and Hamzaoui, Dimitri and Luzurier, Anna and Granger, Benjamin and Montagne, Sarah and Allera, Alexandre and Ezziane, Malek and Quint, Rapha{\"e}le and Kalai, Mehdi and Ayache, Nicholas and Delingette, Herv{\'e} and Renard-Penna, Rapha{\"e}le},
url-hal= {https://hal.science/hal-04185065},
JOURNAL = {{Diagnostic and Interventional Imaging}},
PUBLISHER = {{Elsevier}},
YEAR = {2023},
MONTH = Aug,
DOI = {10.1016/j.diii.2023.08.001},
KEYWORDS = {Artificial intelligence Inter-reader variability Magnetic resonance imaging Prostate Segmentation},
HAL_ID = {hal-04185065},
HAL_VERSION = {v1},
}
-
Théodore Soulier,
Olivier Colliot,
Nicholas Ayache,
and Benjamin Rohaut.
How will tomorrow's algorithms fuse multimodal data? The example of the neuroprognosis in Intensive Care.
Anaesthesia Critical Care & Pain Medicine,
pp 101301,
September 2023.
Keyword(s): Disorders of Consciousness,
Neurological Prognosis,
Multimodal Data,
Artificial Intelligence,
Disorders of Consciousness Neurological Prognosis Multimodal Data Artificial Intelligence.
@article{soulier:hal-04227434,
TITLE = {{How will tomorrow's algorithms fuse multimodal data? The example of the neuroprognosis in Intensive Care}},
AUTHOR = {Soulier, Th{\'e}odore and Colliot, Olivier and Ayache, Nicholas and Rohaut, Benjamin},
url-hal= {https://hal.sorbonne-universite.fr/hal-04227434},
JOURNAL = {{Anaesthesia Critical Care \& Pain Medicine}},
PUBLISHER = {{Elsevier Masson}},
PAGES = {101301},
YEAR = {2023},
MONTH = Sep,
DOI = {10.1016/j.accpm.2023.101301},
KEYWORDS = {Disorders of Consciousness ; Neurological Prognosis ; Multimodal Data ; Artificial Intelligence ; Disorders of Consciousness Neurological Prognosis Multimodal Data Artificial Intelligence},
PDF = {https://hal.sorbonne-universite.fr/hal-04227434/file/manuscript4hal.pdf},
HAL_ID = {hal-04227434},
HAL_VERSION = {v1},
}
-
Yann Thanwerdas and Xavier Pennec.
Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks.
SIAM Journal on Matrix Analysis and Applications,
44(3):1447-1476,
September 2023.
Keyword(s): Covariance matrices,
PSD matrices,
Bures-Wasserstein,
Orbit space,
Geodesics,
Injection domain,
15B48,
15A63,
53B20,
53C22,
58D17,
53-08,
53A04,
54E50,
58A35.
@article{thanwerdas:hal-03647321,
TITLE = {{Bures-Wasserstein minimizing geodesics between covariance matrices of different ranks}},
AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
url-hal= {https://hal.science/hal-03647321},
JOURNAL = {{SIAM Journal on Matrix Analysis and Applications}},
PUBLISHER = {{Society for Industrial and Applied Mathematics}},
VOLUME = {44},
NUMBER = {3},
PAGES = {1447-1476},
YEAR = {2023},
MONTH = Sep,
DOI = {10.1137/22M149168X},
KEYWORDS = {Covariance matrices ; PSD matrices ; Bures-Wasserstein ; Orbit space ; Geodesics ; Injection domain ; 15B48 ; 15A63 ; 53B20 ; 53C22 ; 58D17 ; 53-08 ; 53A04 ; 54E50 ; 58A35},
PDF = {https://hal.science/hal-03647321/file/main.pdf},
HAL_ID = {hal-03647321},
HAL_VERSION = {v1},
}
-
Yann Thanwerdas and Xavier Pennec.
O(n)-invariant Riemannian metrics on SPD matrices.
Linear Algebra and its Applications,
661:163-201,
March 2023.
Keyword(s): 53B20,
Symmetric Positive Definite matrices,
Riemannian geometry,
Invariance under orthogonal transformations,
Families of metrics,
Log-Euclidean metric,
Affine-invariant metric,
Bures-Wasserstein metric,
Kernel metrics.
@article{thanwerdas:hal-03338601,
TITLE = {{O(n)-invariant Riemannian metrics on SPD matrices}},
AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
url-hal= {https://hal.science/hal-03338601},
JOURNAL = {{Linear Algebra and its Applications}},
PUBLISHER = {{Elsevier}},
VOLUME = {661},
PAGES = {163-201},
YEAR = {2023},
MONTH = Mar,
DOI = {10.1016/j.laa.2022.12.009},
KEYWORDS = {53B20 ; Symmetric Positive Definite matrices ; Riemannian geometry ; Invariance under orthogonal transformations ; Families of metrics ; Log-Euclidean metric ; Affine-invariant metric ; Bures-Wasserstein metric ; Kernel metrics},
PDF = {https://hal.science/hal-03338601v3/file/LAA_YT_XP_O_n_invariant_metrics_v3%20%282%29.pdf},
HAL_ID = {hal-03338601},
HAL_VERSION = {v3},
}
-
Paul Tourniaire,
Marius Ilie,
Paul Hofman,
Nicholas Ayache,
and Hervé Delingette.
MS-CLAM: Mixed Supervision for the classification and localization of tumors in Whole Slide Images.
Medical Image Analysis,
85:102763,
2023.
Keyword(s): Digital Pathology,
Mixed Supervision,
Deep Learning,
Camelyon16,
DigestPath2019.
@article{tourniaire:hal-03972289,
TITLE = {{MS-CLAM: Mixed Supervision for the classification and localization of tumors in Whole Slide Images}},
AUTHOR = {Tourniaire, Paul and Ilie, Marius and Hofman, Paul and Ayache, Nicholas and Delingette, Herv{\'e}},
url-hal= {https://inria.hal.science/hal-03972289},
JOURNAL = {{Medical Image Analysis}},
PUBLISHER = {{Elsevier}},
VOLUME = {85},
PAGES = {102763},
YEAR = {2023},
DOI = {10.1016/j.media.2023.102763},
KEYWORDS = {Digital Pathology ; Mixed Supervision ; Deep Learning ; Camelyon16 ; DigestPath2019},
PDF = {https://inria.hal.science/hal-03972289/file/article_MedIA_hal_version.pdf},
HAL_ID = {hal-03972289},
HAL_VERSION = {v1},
}
-
Zihao Wang,
Zhifei Xu,
Jiayi He,
Herve Delingette,
and Jun Fan.
Long Short-Term Memory Neural Equalizer.
IEEE Transactions on Signal and Power Integrity,
2:13-22,
2023.
@article{wang:hal-04042921,
TITLE = {{Long Short-Term Memory Neural Equalizer}},
AUTHOR = {Wang, Zihao and Xu, Zhifei and He, Jiayi and Delingette, Herve and Fan, Jun},
url-hal= {https://inria.hal.science/hal-04042921},
JOURNAL = {{IEEE Transactions on Signal and Power Integrity}},
VOLUME = {2},
PAGES = {13-22},
YEAR = {2023},
DOI = {10.1109/TSIPI.2023.3242855},
HAL_ID = {hal-04042921},
HAL_VERSION = {v1},
}
-
Marco Lorenzi,
Marie Deprez,
Irene Balelli,
Ana L Aguila,
and Andre Altmann.
Integration of Multimodal Data.
In Olivier Colliot, editor, Machine Learning for Brain Disorders,
volume NM197 of Neuromethods,
pages 573 - 597.
Springer,
2023.
Keyword(s): Multivariate analysis,
Latent variable models,
Multimodal imaging,
-Omics,
Imaginggenetics,
Partial least squares,
Canonical correlation analysis,
Variational autoencoders,
Sparsity,
Interpretability.
@incollection{lorenzi:hal-04239814,
TITLE = {{Integration of Multimodal Data}},
AUTHOR = {Lorenzi, Marco and Deprez, Marie and Balelli, Irene and Aguila, Ana L and Altmann, Andre},
url-hal= {https://hal.science/hal-04239814},
BOOKTITLE = {{Machine Learning for Brain Disorders}},
EDITOR = {Olivier Colliot},
PUBLISHER = {{Springer}},
SERIES = {Neuromethods},
VOLUME = {NM197},
PAGES = {573 - 597},
YEAR = {2023},
DOI = {10.1007/978-1-0716-3195-9\_19},
KEYWORDS = {Multivariate analysis ; Latent variable models ; Multimodal imaging ; -Omics ; Imaginggenetics ; Partial least squares ; Canonical correlation analysis ; Variational autoencoders ; Sparsity ; Interpretability},
PDF = {https://hal.science/hal-04239814/file/Chapter19.pdf},
HAL_ID = {hal-04239814},
HAL_VERSION = {v1},
}
-
Buntheng Ly,
Mihaela Pop,
Hubert Cochet,
Nicolas Duchateau,
Declan O'regan,
and Maxime Sermesant.
Outcome Prediction.
In AI and Big Data in Cardiology : A Practical Guide,
pages 105-133.
Springer International Publishing,
May 2023.
@incollection{ly:hal-04212068,
TITLE = {{Outcome Prediction}},
AUTHOR = {Ly, Buntheng and Pop, Mihaela and Cochet, Hubert and Duchateau, Nicolas and O'regan, Declan and Sermesant, Maxime},
url-hal= {https://hal.science/hal-04212068},
BOOKTITLE = {{AI and Big Data in Cardiology : A Practical Guide}},
PUBLISHER = {{Springer International Publishing}},
PAGES = {105-133},
YEAR = {2023},
MONTH = May,
DOI = {10.1007/978-3-031-05071-8\_6},
HAL_ID = {hal-04212068},
HAL_VERSION = {v1},
}
-
Morten Akhoj,
Xavier Pennec,
and Stefan Sommer.
Tangent phylogenetic PCA.
In Scandinavian Conference on Image Analysis 2023,
Levi Ski Resort (Lapland), Finland,
April 2023.
@inproceedings{akhoj:hal-03842847,
TITLE = {{Tangent phylogenetic PCA}},
AUTHOR = {Akh{{\o}}j, Morten and Pennec, Xavier and Sommer, Stefan},
url-hal= {https://inria.hal.science/hal-03842847},
BOOKTITLE = {{Scandinavian Conference on Image Analysis 2023}},
ADDRESS = {Levi Ski Resort (Lapland), Finland},
YEAR = {2023},
MONTH = Apr,
PDF = {https://inria.hal.science/hal-03842847/file/2208.12730.pdf},
HAL_ID = {hal-03842847},
HAL_VERSION = {v1},
}
-
Anna Calissano,
Elodie Maignant,
and Xavier Pennec.
Towards Quotient Barycentric Subspaces.
In GSI 2023: Geometric Science of Information,
volume 14071 of Lecture Notes in Computer Science,
Saint-Malo (France), France,
pages 366-374,
August 2023.
Springer Nature Switzerland.
Keyword(s): Discrete Group,
Quotient Space,
Barycentric Subspace Analysis,
Graph Space,
Object Oriented Data Analysis.
@inproceedings{calissano:hal-04162647,
TITLE = {{Towards Quotient Barycentric Subspaces}},
AUTHOR = {Calissano, Anna and Maignant, Elodie and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04162647},
BOOKTITLE = {{GSI 2023: Geometric Science of Information}},
ADDRESS = {Saint-Malo (France), France},
PUBLISHER = {{Springer Nature Switzerland}},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {14071},
PAGES = {366-374},
YEAR = {2023},
MONTH = Aug,
DOI = {10.1007/978-3-031-38271-0\_36},
KEYWORDS = {Discrete Group ; Quotient Space ; Barycentric Subspace Analysis ; Graph Space ; Object Oriented Data Analysis},
PDF = {https://inria.hal.science/hal-04162647/file/Towards_Quotient_Barycentric_Subspaces.pdf},
HAL_ID = {hal-04162647},
HAL_VERSION = {v1},
}
-
Nicolas Cedilnik and Jean-Marc Peyrat.
Weighted tissue thickness.
In FIMH 2023 - 12th International Conference On Functional Imaging And Modeling Of The Heart,
Lecture Notes in Computer Science,
Lyon, France,
June 2023.
Springer.
Keyword(s): Thickness,
Thickness measurements,
Medical image analysis.
@inproceedings{cedilnik:hal-04111276,
TITLE = {{Weighted tissue thickness}},
AUTHOR = {Cedilnik, Nicolas and Peyrat, Jean-Marc},
url-hal= {https://inria.hal.science/hal-04111276},
BOOKTITLE = {{FIMH 2023 - 12th International Conference On Functional Imaging And Modeling Of The Heart}},
ADDRESS = {Lyon, France},
PUBLISHER = {{Springer}},
SERIES = {Lecture Notes in Computer Science},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Thickness ; Thickness measurements ; Medical image analysis},
PDF = {https://inria.hal.science/hal-04111276/file/article.pdf},
HAL_ID = {hal-04111276},
HAL_VERSION = {v1},
}
-
Hind Dadoun,
Hervé Delingette,
Anne-Laure Rousseau,
Eric de Kerviler,
and Nicholas Ayache.
Joint representation learning from french radiological reports and ultrasound images.
In IEEE ISBI 2023 - International Symposium on Biomedical Imaging,
Cartagena de Indias, Colombia,
April 2023.
IEEE.
Keyword(s): multimodal learning deep clustering natural language processing ultrasound examinations kidneys,
multimodal learning,
deep clustering,
natural language processing,
ultrasound examinations,
kidneys.
@inproceedings{dadoun:hal-03984528,
TITLE = {{Joint representation learning from french radiological reports and ultrasound images}},
AUTHOR = {Dadoun, Hind and Delingette, Herv{\'e} and Rousseau, Anne-Laure and de Kerviler, Eric and Ayache, Nicholas},
url-hal= {https://inria.hal.science/hal-03984528},
BOOKTITLE = {{IEEE ISBI 2023 - International Symposium on Biomedical Imaging}},
ADDRESS = {Cartagena de Indias, Colombia},
ORGANIZATION = {{IEEE}},
YEAR = {2023},
MONTH = Apr,
KEYWORDS = {multimodal learning deep clustering natural language processing ultrasound examinations kidneys ; multimodal learning ; deep clustering ; natural language processing ; ultrasound examinations ; kidneys},
PDF = {https://inria.hal.science/hal-03984528/file/HIND_DADOUN_ISBI_2023.pdf},
HAL_ID = {hal-03984528},
HAL_VERSION = {v1},
}
-
Zhijie Fang,
Hervé Delingette,
and Nicholas Ayache.
Anatomical Landmark Detection for Initializing US and MR Image Registration.
In MICCAI ASMUS 2023 - 4th International Workshop of Advances in Simplifying Medical UltraSound - a workshop held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer Assisted Intervention,
Vancouver, Canada,
October 2023.
Keyword(s): Landmark detection,
Image-guided intervention,
Convolutional neural network and Prostate cancer.
@inproceedings{fang:hal-04189905,
TITLE = {{Anatomical Landmark Detection for Initializing US and MR Image Registration}},
AUTHOR = {Fang, Zhijie and Delingette, Herv{\'e} and Ayache, Nicholas},
url-hal= {https://hal.science/hal-04189905},
BOOKTITLE = {{MICCAI ASMUS 2023 - 4th International Workshop of Advances in Simplifying Medical UltraSound - a workshop held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer Assisted Intervention}},
ADDRESS = {Vancouver, Canada},
YEAR = {2023},
MONTH = Oct,
KEYWORDS = {Landmark detection ; Image-guided intervention ; Convolutional neural network and Prostate cancer},
PDF = {https://hal.science/hal-04189905/file/Fang-ASMUS-camera-ready-version-18Aug2023.pdf},
HAL_ID = {hal-04189905},
HAL_VERSION = {v1},
}
-
Elodie Maignant,
Alain Trouvé,
and Xavier Pennec.
Riemannian Locally Linear Embedding with Application to Kendall Shape Spaces.
In GSI 2023: Geometric Science of Information,
volume 14071 of Lecture Notes in Computer Science,
Saint-Malo, (France), France,
pages 12-20,
August 2023.
Springer Nature Switzerland.
Keyword(s): Locally Linear Embedding,
Optimisation on Quotient Manifolds,
Shape Spaces.
@inproceedings{maignant:hal-04122754,
TITLE = {{Riemannian Locally Linear Embedding with Application to Kendall Shape Spaces}},
AUTHOR = {Maignant, Elodie and Trouv{\'e}, Alain and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04122754},
BOOKTITLE = {{GSI 2023: Geometric Science of Information}},
ADDRESS = {Saint-Malo, (France), France},
PUBLISHER = {{Springer Nature Switzerland}},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {14071},
PAGES = {12-20},
YEAR = {2023},
MONTH = Aug,
DOI = {10.1007/978-3-031-38271-0\_2},
KEYWORDS = {Locally Linear Embedding ; Optimisation on Quotient Manifolds ; Shape Spaces},
PDF = {https://inria.hal.science/hal-04122754/file/Riemannian_Locally_Linear_Embedding_with_Application_to_Kendall_Shape_Spaces.pdf},
HAL_ID = {hal-04122754},
HAL_VERSION = {v1},
}
-
Hari Sreedhar,
Guillaume P R Lajoinie,
Charles Raffaelli,
and Hervé Delingette.
Active Learning Strategies on a Real-World Thyroid Ultrasound Dataset.
In DALI 2023 - Data Augmentation, Labelling, and Imperfections / MICCAI Workshop 2023,
MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2023, held in conjunction with MICCAI 2023 Proceedings,
Vancouver, Canada,
October 2023.
Keyword(s): Thyroid cancer,
Active learning,
Ultrasound imaging.
@inproceedings{sreedhar:hal-04209622,
TITLE = {{Active Learning Strategies on a Real-World Thyroid Ultrasound Dataset}},
AUTHOR = {Sreedhar, Hari and Lajoinie, Guillaume P R and Raffaelli, Charles and Delingette, Herv{\'e}},
url-hal= {https://inria.hal.science/hal-04209622},
BOOKTITLE = {{DALI 2023 - Data Augmentation, Labelling, and Imperfections / MICCAI Workshop 2023}},
ADDRESS = {Vancouver, Canada},
SERIES = {MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2023, held in conjunction with MICCAI 2023 Proceedings},
YEAR = {2023},
MONTH = Oct,
KEYWORDS = {Thyroid cancer ; Active learning ; Ultrasound imaging},
PDF = {https://inria.hal.science/hal-04209622/file/manuscript.pdf},
HAL_ID = {hal-04209622},
HAL_VERSION = {v1},
}
-
Tom Szwagier and Xavier Pennec.
Rethinking the Riemannian Logarithm on Flag Manifolds as an Orthogonal Alignment Problem.
In GSI 2023: Geometric Science of Information,
volume 14071 of Lecture Notes in Computer Science,
Saint-Malo, (France), France,
pages 375-383,
August 2023.
Springer Nature Switzerland.
Keyword(s): Flag manifolds,
Riemannian logarithm,
Orthogonal alignment,
Procrustes analysis,
Flag manifolds Riemannian logarithm Orthogonal alignment Procrustes analysis.
@inproceedings{szwagier:hal-04100534,
TITLE = {{Rethinking the Riemannian Logarithm on Flag Manifolds as an Orthogonal Alignment Problem}},
AUTHOR = {Szwagier, Tom and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04100534},
BOOKTITLE = {{GSI 2023: Geometric Science of Information}},
ADDRESS = {Saint-Malo, (France), France},
PUBLISHER = {{Springer Nature Switzerland}},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {14071},
PAGES = {375-383},
YEAR = {2023},
MONTH = Aug,
DOI = {10.1007/978-3-031-38271-0\_37},
KEYWORDS = {Flag manifolds ; Riemannian logarithm ; Orthogonal alignment ; Procrustes analysis ; Flag manifolds Riemannian logarithm Orthogonal alignment Procrustes analysis},
PDF = {https://inria.hal.science/hal-04100534/file/GSI-119.pdf},
HAL_ID = {hal-04100534},
HAL_VERSION = {v1},
}
-
Yann Thanwerdas and Xavier Pennec.
Characterization of Invariant Inner Products.
In GSI 2023 - International Conference on Geometric Science of Information,
volume LNCS-14071 of Geometric Science of Information: 6th International Conference, GSI 2023, St. Malo, France, August 30 -- September 1, 2023, Proceedings, Part I,
Saint Malo, France, France,
pages 384-391,
August 2023.
Springer Nature Switzerland.
Keyword(s): Invariant inner product Invariant Riemannian metric Group action Representation theory,
Invariant inner product,
Invariant Riemannian metric,
Group action,
Representation theory.
@inproceedings{thanwerdas:hal-04229093,
TITLE = {{Characterization of Invariant Inner Products}},
AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04229093},
BOOKTITLE = {{GSI 2023 - International Conference on Geometric Science of Information}},
ADDRESS = {Saint Malo, France, France},
PUBLISHER = {{Springer Nature Switzerland}},
SERIES = {Geometric Science of Information: 6th International Conference, GSI 2023, St. Malo, France, August 30 -- September 1, 2023, Proceedings, Part I},
VOLUME = {LNCS-14071},
PAGES = {384-391},
YEAR = {2023},
MONTH = Aug,
DOI = {10.1007/978-3-031-38271-0\_38},
KEYWORDS = {Invariant inner product Invariant Riemannian metric Group action Representation theory ; Invariant inner product ; Invariant Riemannian metric ; Group action ; Representation theory},
PDF = {https://inria.hal.science/hal-04229093/file/GSI-105.pdf},
HAL_ID = {hal-04229093},
HAL_VERSION = {v1},
}
-
Yingyu Yang and Maxime Sermesant.
Unsupervised Polyaffine Transformation Learning for Echocardiography Motion Estimation.
In FIMH 2023 - The 12th International Conference on Functional Imaging and Modeling of The Heart,
Lyon, France,
June 2023.
Keyword(s): Motion Estimation Echocardiography Polyaffine Transformation,
Motion Estimation,
Echocardiography,
Polyaffine Transformation.
@inproceedings{yang:hal-04109721,
TITLE = {{Unsupervised Polyaffine Transformation Learning for Echocardiography Motion Estimation}},
AUTHOR = {Yang, Yingyu and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-04109721},
BOOKTITLE = {{FIMH 2023 - The 12th International Conference on Functional Imaging and Modeling of The Heart}},
ADDRESS = {Lyon, France},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Motion Estimation Echocardiography Polyaffine Transformation ; Motion Estimation ; Echocardiography ; Polyaffine Transformation},
PDF = {https://inria.hal.science/hal-04109721/file/Unsupervised_Polyaffine_Motion_Model_for_Echocardiography_Analysis__final_-2.pdf},
HAL_ID = {hal-04109721},
HAL_VERSION = {v1},
}
-
Yanis Aeschlimann,
Anna Calissano,
Samuel Deslauriers-Gauthier,
Théodore Papadopoulo,
and Andreas Hansen.
Preliminary results on the graph matching of structural and functional brain networks.
Neuromod Yearly Meeting 2023,
June 2023.
Note: Poster.
Keyword(s): brain networks,
structural connectivity,
functional connectivity,
brain atlas,
network alignment.
@misc{aeschlimann:hal-04165209,
TITLE = {{Preliminary results on the graph matching of structural and functional brain networks}},
AUTHOR = {Aeschlimann, Yanis and Calissano, Anna and Deslauriers-Gauthier, Samuel and Papadopoulo, Th{\'e}odore and Hansen, Andreas},
url-hal= {https://inria.hal.science/hal-04165209},
NOTE = {Poster},
HOWPUBLISHED = {{Neuromod Yearly Meeting 2023}},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {brain networks ; structural connectivity ; functional connectivity ; brain atlas ; network alignment},
PDF = {https://inria.hal.science/hal-04165209/file/Neuromod_2023_poster_Yanis_AESCHLIMANN.pdf},
HAL_ID = {hal-04165209},
HAL_VERSION = {v1},
}
-
Morten Akhoj,
James Benn,
Erlend Grong,
Stefan Sommer,
and Xavier Pennec.
Principal subbundles for dimension reduction.
Note: Working paper or preprint,
July 2023.
@unpublished{akhoj:hal-04156036,
TITLE = {{Principal subbundles for dimension reduction}},
AUTHOR = {Akh{{\o}}j, Morten and Benn, James and Grong, Erlend and Sommer, Stefan and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04156036},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Jul,
HAL_ID = {hal-04156036},
HAL_VERSION = {v1},
}
-
Safaa Al-Ali,
Jordi Llopis-Lorente,
Maria Teresa Mora,
Maxime Sermesant,
Beatriz Trénor,
and Irene Balelli.
A causal discovery approach for streamline ion channels selection to improve drug-induced TdP risk assessment.
Note: Working paper or preprint,
2023.
Keyword(s): Causal discovery,
Drug safety,
Ions channel,
TdP risk.
@unpublished{alali:hal-04105144,
TITLE = {{A causal discovery approach for streamline ion channels selection to improve drug-induced TdP risk assessment}},
AUTHOR = {Al-Ali, Safaa and Llopis-Lorente, Jordi and Mora, Maria Teresa and Sermesant, Maxime and Tr{\'e}nor, Beatriz and Balelli, Irene},
url-hal= {https://hal.science/hal-04105144},
NOTE = {working paper or preprint},
YEAR = {2023},
KEYWORDS = {Causal discovery ; Drug safety ; Ions channel ; TdP risk},
PDF = {https://hal.science/hal-04105144/file/Draft_CMSB_Sept_2023-2.pdf},
HAL_ID = {hal-04105144},
HAL_VERSION = {v1},
}
-
Irene Balelli,
Aude Sportisse,
Francesco Cremonesi,
Pierre-Alexandre Mattei,
and Marco Lorenzi.
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models.
Note: Working paper or preprint,
2023.
Keyword(s): Missing data,
Federated learning,
Federated pre-processing,
Variational autoencoders,
Deep Learning.
@unpublished{balelli:hal-04069795,
TITLE = {{Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models}},
AUTHOR = {Balelli, Irene and Sportisse, Aude and Cremonesi, Francesco and Mattei, Pierre-Alexandre and Lorenzi, Marco},
url-hal= {https://hal.science/hal-04069795},
NOTE = {working paper or preprint},
YEAR = {2023},
KEYWORDS = {Missing data ; Federated learning ; Federated pre-processing ; Variational autoencoders ; Deep Learning},
PDF = {https://hal.science/hal-04069795/file/main_MICCAI.pdf},
HAL_ID = {hal-04069795},
HAL_VERSION = {v1},
}
-
Blanche Buet and Xavier Pennec.
Flagfolds.
Note: Working paper or preprint,
2023.
@unpublished{buet:hal-04112465,
TITLE = {{Flagfolds}},
AUTHOR = {Buet, Blanche and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04112465},
NOTE = {working paper or preprint},
YEAR = {2023},
HAL_ID = {hal-04112465},
HAL_VERSION = {v1},
}
-
Francesco Cremonesi,
Marc Vesin,
Sergen Cansiz,
Yannick Bouillard,
Irene Balelli,
Lucia Innocenti,
Santiago Silva,
Samy-Safwan Ayed,
Riccardo Taiello,
Laetita Kameni,
Richard Vidal,
Fanny Orlhac,
Christophe Nioche,
Nathan Lapel,
Bastien Houis,
Romain Modzelewski,
Olivier Humbert,
Melek Önen,
and Marco Lorenzi.
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications.
Note: Working paper or preprint,
April 2023.
Keyword(s): Machine learning,
Biomedical Application,
Healthcare,
Federated Learning Framework.
@unpublished{cremonesi:hal-04081557,
TITLE = {{Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications}},
AUTHOR = {Cremonesi, Francesco and Vesin, Marc and Cansiz, Sergen and Bouillard, Yannick and Balelli, Irene and Innocenti, Lucia and Silva, Santiago and Ayed, Samy-Safwan and Taiello, Riccardo and Kameni, Laetita and Vidal, Richard and Orlhac, Fanny and Nioche, Christophe and Lapel, Nathan and Houis, Bastien and Modzelewski, Romain and Humbert, Olivier and {\"O}nen, Melek and Lorenzi, Marco},
url-hal= {https://inria.hal.science/hal-04081557},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Apr,
KEYWORDS = {Machine learning ; Biomedical Application ; Healthcare ; Federated Learning Framework},
PDF = {https://inria.hal.science/hal-04081557/file/fedbiomed_paper-5.pdf},
HAL_ID = {hal-04081557},
HAL_VERSION = {v1},
}
-
Etrit Haxholli and Marco Lorenzi.
Faster Training and Improved Performance of Diffusion Models via Parallel Score Matching.
Note: Working paper or preprint,
March 2023.
@unpublished{haxholli:hal-04032669,
TITLE = {{Faster Training and Improved Performance of Diffusion Models via Parallel Score Matching}},
AUTHOR = {Haxholli, Etrit and Lorenzi, Marco},
url-hal= {https://inria.hal.science/hal-04032669},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Mar,
HAL_ID = {hal-04032669},
HAL_VERSION = {v1},
}
-
Dimbihery Rabenoro and Xavier Pennec.
The geometry of Riemannian submersions from compact Lie groups. Application to flag manifolds.
Note: Working paper or preprint,
October 2023.
@unpublished{rabenoro:hal-04232479,
TITLE = {{The geometry of Riemannian submersions from compact Lie groups. Application to flag manifolds}},
AUTHOR = {Rabenoro, Dimbihery and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04232479},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Oct,
PDF = {https://inria.hal.science/hal-04232479/file/2302.14810-1.pdf},
HAL_ID = {hal-04232479},
HAL_VERSION = {v1},
}
-
Tom Szwagier and Xavier Pennec.
Stratified principal component analysis.
Note: Working paper or preprint,
November 2023.
Keyword(s): Covariance model,
Eigenvalue multiplicity,
Flag manifold,
Parsimony,
Probabilistic principal component analysis,
Stratification.
@unpublished{szwagier:hal-04171853,
TITLE = {{Stratified principal component analysis}},
AUTHOR = {Szwagier, Tom and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04171853},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Nov,
KEYWORDS = {Covariance model ; Eigenvalue multiplicity ; Flag manifold ; Parsimony ; Probabilistic principal component analysis ; Stratification},
PDF = {https://inria.hal.science/hal-04171853v2/file/Stratified-PCA.pdf},
HAL_ID = {hal-04171853},
HAL_VERSION = {v2},
}
-
Yann Thanwerdas.
Permutation-invariant log-Euclidean geometries on full-rank correlation matrices.
Note: Working paper or preprint,
November 2023.
Keyword(s): SPD matrices,
elliptope,
correlation matrices,
log-Euclidean metric,
permutationinvariant,
cor-inversion,
off-log metric,
log-scaled metric,
quotient-affine metric AMS subject classifications.,
15A63,
53B20,
53C22,
58D17,
53-08,
53A04,
62H20,
15B48.
@unpublished{thanwerdas:hal-03878729,
TITLE = {{Permutation-invariant log-Euclidean geometries on full-rank correlation matrices}},
AUTHOR = {Thanwerdas, Yann},
url-hal= {https://hal.science/hal-03878729},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Nov,
KEYWORDS = {SPD matrices ; elliptope ; correlation matrices ; log-Euclidean metric ; permutationinvariant ; cor-inversion ; off-log metric ; log-scaled metric ; quotient-affine metric AMS subject classifications. ; 15A63 ; 53B20 ; 53C22 ; 58D17 ; 53-08 ; 53A04 ; 62H20 ; 15B48},
PDF = {https://hal.science/hal-03878729v2/file/SIMAX_YT_Log_Euclidean_correlation_v3.pdf},
HAL_ID = {hal-03878729},
HAL_VERSION = {v2},
}