Edouard Duchesnay
- NeuroSpin/GAIA (Brain Imaging and Data Science Lab) (NeuroSpin/GAIA)
Présentation
As a leader of the team “Signatures of brain disorders” at NeuroSpin, CEA, Université Paris-Saclay, France, I supervise the design of machine learning and statistical models to uncover neural signatures predictive of clinical trajectories in psychiatric disorders. To unlock the access to data required by learning algorithms, I oversee the data management, calculation, and regulation (GDPR) of large-scale national and European initiatives.
Domaines de recherche
Compétences
Publications
Publications
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Does Connectome Harmonic Analysis Pass the Spin Test?Medical Image Computing and Computer Assisted Intervention – MICCAI 2025, Sep 2025, Daejeon, South Korea. pp.279-287, ⟨10.1007/978-3-032-05162-2_27⟩ |
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Supervised diagnosis prediction from cortical sulci: toward the discovery of neurodevelopmental biomarkers in mental disorders21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), IEEE, May 2024, Athènes, Greece |
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SepVAE: a contrastive VAE to separate pathological patterns from healthy onesMedical Imaging with Deep Learning (MIDL), Jul 2024, Paris, France. ⟨10.48550/arXiv.2307.06206⟩ |
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Separating common from salient patterns with Contrastive Representation LearningInternational Conference on Learning Representations (ICLR), May 2024, Vienna, Austria |
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How and why does deep ensemble coupled with transfer learning increase performance in bipolar disorder and schizophrenia classification?ISBI 2024 - IEEE International Symposium on Biomedical Imaging, May 2024, Athenes, Greece |
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Multi-view variational autoencoders allow for interpretability leveraging digital Avatars: application to the HBN cohortISBI 2023 - 2023 IEEE 20th International Symposium on Biomedical Imaging ISBI, Apr 2023, Cartagene, Colombia. pp.1-5, ⟨10.1109/ISBI53787.2023.10230552⟩ |
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CONTRASTIVE LEARNING FOR REGRESSION IN MULTI-SITE BRAIN AGE PREDICTIONIEEE ISBI (International Symposium on Biomedical Imaging ), Apr 2023, Cartagena de Indias, Colombia |
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MixUp brain-cortical augmentations in self-supervised learningMedical Image Computing and Computer Assisted Intervention, Oct 2023, Vancouver, Canada. pp.102-111, ⟨10.1007/978-3-031-44858-4_10⟩ |
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Integrating Prior Knowledge in Contrastive Learning with Kernel40 th International Conference on Machine Learning, Jul 2023, Honolulu, United States |
Do neuroplasticity and genetic factors contribute to cognitive training? An imaging-genetics study in healthy childrenThe international Congress fot integrative developmental cognitive neuroscience FLUX 2022, Sep 2022, Paris, France |
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UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised LearningECML/PKDD, Sep 2021, Bilbao, Spain |
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Conditional Alignment and Uniformity for Contrastive Learning with Continuous Proxy LabelsMed-NeurIPS - Workshop NeurIPS, Dec 2021, Vancouver, Canada |
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Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI ClassificationMICCAI, Sep 2021, Strasbourg (virtuel), France |
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Interpretable and stable prediction of schizophrenia on a large multisite dataset using machine learning with structured sparsity2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI), Jun 2018, Singapore, Singapore. ⟨10.1109/PRNI.2018.8423946⟩ |
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Regional study of the genetic influence on the sulcal pits2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), Apr 2017, Melbourne, France. ⟨10.1109/ISBI.2017.7950472⟩ |
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Voxelwise genome-wide association study on gray matter volume reveals a SLC39A8 variant associated with subcortical structuresJournées RITS 2015, Mar 2015, Dourdan, France. p32-32 Section imagerie génétique |
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Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI2014 International Workshop on Pattern Recognition in Neuroimaging, Jun 2014, Tuebingen, Germany. pp.1-4, ⟨10.1109/PRNI.2014.6858517⟩ |
Structured variable selection for generalized canonical correlation analysisPLS’14, May 2014, Paris, France |
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A multi-block approach in imaging genetics9th International Imaging Genetics Conference, Jan 2013, Irvine, California, United States. pp.Poster 13 |
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A fast computational framework for genome-wide association studies with neuroimaging data20th International Conference on Computational Statistics (COMPSTAT 2012), Aug 2012, Limassol, Cyprus |
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Structured Multivariate Pattern Classification to Detect MRI Markers for an Early Diagnosis of Alzheimer's Disease2011 Tenth International Conference on Machine Learning and Applications (ICMLA 2011), Dec 2011, Honolulu, United States. pp.384-387, ⟨10.1109/ICMLA.2011.185⟩ |
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Imaging genetics: bio-informatics and bio-statistics challenges19th International Conference on Computational Statistics, Aug 2010, Paris, France |
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Do neuroplasticity and genetic factors contribute to cognitive training ? An imaging-genetics study in healthy children.FLUX congress, Sep 2022, Paris, France |
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Do neuroplasticity and genetic factors contribute to cognitive training in children?OHBM ( Organization for Human Brain Mapping) 2022 Annual Meeting, Jun 2022, Glasgow, United Kingdom |
Structured Variable Selection for Regularized Generalized Canonical Correlation Analysis, The Multiple Facets of Partial Least Squares and Related MethodsSpringer Proceedings in Mathematics & Statistics, pp.129-139, 2016, The Multiple Facets of Partial Least Squares and Related Methods, ⟨10.1007/978-3-319-40643-5_10⟩ |
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Dimension Reduction and Regularization Combined with Partial Least Squares in High Dimensional Imaging Genetics StudiesNew Perspectives in Partial Least Squares and Related Methods, Springer, pp.147-158, 2013, Springer Proceedings in Mathematics & Statistics, ⟨10.1007/978-1-4614-8283-3_9⟩ |
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Bridging genetics and neuroimaging: Polygenic risk score integration with the view to perform weakly supervised learning2025 |
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Cortical sulci are regional neurodevelopmental biomarkers of schizophrenia diagnosis2024 |
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Supplementary material: Continuation of Nesterov's Smoothing for Regression with Structured Sparsity in High-Dimensional Neuroimaging2016 |
Structured variable selection for generalized canonical correlation analysis2015 |
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Simulated Data for Linear Regression with Structured and Sparse Penalties2014 |
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Agents situés dans l'image et organisés en pyramide irrégulière: Contribution à la segmentation par une approche d'agrégation coopérative et adaptativeIntelligence artificielle [cs.AI]. Université Rennes 1, 2001. Français. ⟨NNT : ⟩ |
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Neuroimaging signatures of brain disorders: Fighting overfitting in predictive modelsMachine Learning [stat.ML]. Université Paris-Saclay, FRA., 2020 |
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Statistics and Machine Learning in PythonEngineering school. France. 2025 |