Olivier Colliot
Olivier Colliot - Research Director at CNRS - ARAMIS Lab at the Paris Brain Institute (CNRS/Inria/Inserm/Sorbonne Universite)
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Documents
Identifiants chercheurs
- olivier-colliot
- ResearcherId : B-2092-2012
- 0000-0002-9836-654X
- IdRef : 085263893
- Arxiv : colliot_o_1
- ResearcherId : http://www.researcherid.com/rid/B-2092-2012
Présentation
Research Director at [CNRS](http://www.cnrs.fr/)
Head of the [ARAMIS Lab](http://www.aramislab.fr/), a joint team between [CNRS](http://www.cnrs.fr/), [Inria](http://www.inria.fr/), [Inserm](http://www.inserm.fr/) and [University Pierre and Marie Curie](http://www.upmc.fr/) at the [Paris Brain Institute (ICM)](http://www.icm-institute.org/), in co-direction with Stanley Durrleman.
Homepage: <https://www.aramislab.fr/perso/colliot/>
Email: olivier.colliot@cnrs.fr
Research Director at [CNRS](http://www.cnrs.fr/)
Head of the [ARAMIS Lab](http://www.aramislab.fr/), a joint team between [CNRS](http://www.cnrs.fr/), [Inria](http://www.inria.fr/), [Inserm](http://www.inserm.fr/) and [University Pierre and Marie Curie](http://www.upmc.fr/) at the [Paris Brain Institute (ICM)](http://www.icm-institute.org/), in co-direction with Stanley Durrleman.
Homepage: <https://www.aramislab.fr/perso/colliot/>
Email: olivier.colliot@cnrs.fr
Domaines de recherche
Intelligence artificielle [cs.AI]
Imagerie médicale
Apprentissage [cs.LG]
Traitement des images [eess.IV]
Publications
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AD Course Map charts Alzheimer’s disease progressionScientific Reports, 2021, 11 (1), ⟨10.1038/s41598-021-87434-1⟩
Article dans une revue
hal-01964821v3
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Gaussian Graphical Model exploration and selection in high dimension low sample size settingIEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43 (9), pp.3196-3213. ⟨10.1109/TPAMI.2020.2980542⟩
Article dans une revue
hal-02504034v1
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Spatiotemporal Propagation of the Cortical Atrophy: Population and Individual PatternsFrontiers in Neurology, 2018, 9, pp.235. ⟨10.3389/fneur.2018.00235⟩
Article dans une revue
hal-01910400v1
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A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observationsJournal of Machine Learning Research, 2017, 18, pp.1-33
Article dans une revue
hal-01540367v3
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Deciphering the progression of PET alterations using surface-based spatiotemporal modelingOHBM 2019 - Annual meeting of the Organization for Human Brain Mapping, Jun 2019, Rome, Italy
Communication dans un congrès
hal-02134909v1
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Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networksMedical Image Computing and Computer Assisted Intervention, Sep 2017, Quebec City, Canada
Communication dans un congrès
hal-01540828v1
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Learning spatiotemporal trajectories from manifold-valued longitudinal dataNeural Information Processing Systems, Dec 2015, Montréal, Canada
Communication dans un congrès
hal-01163373v3
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A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued dataIPMI - Information Processing in Medical Imaging
Communication dans un congrès
hal-01163213v1
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Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data5th MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Oct 2015, Munich, Germany
Communication dans un congrès
hal-01245905v1
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Learning spatio-temporal trajectories from manifold-valued longitudinal dataNeural Information Processing Systems, Dec 2015, Montréal, Canada. , Advances in Neural Information Processing Systems
Poster de conférence
hal-01245909v1
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