PGMO PhD Prize for Maturin

Maturin Massias, former PhD student of Parietal, is receiving the PGMO PhD Prize for his work  “Sparse high dimensional regression in the presence of colored heteroscedastic noise : application to M/EEG source imaging” and implementation of his ideas in CELER (

Congratulations !

6 papers at NeurIPS 2020

We’re delighted to announce that the following 6 papers have been accepted at NeurIPS:

  • Entropic Optimal Transport between (Unbalanced) Gaussian Measures has a Closed Form Hicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi
  • Modeling shared responses in Neuroimaging Studies through MultiViewICA. Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin.
  • PEP: Parameter Ensembling by Perturbation. Alireza Mehrtash, Purang Abolmaesumi, Polina Golland, Tina Kapur, Demian Wassermann, William Wells.
  • Leaning to solve TV regularised problems with unrolled algorithms. Hamza Cherkaoui, Jeremias Sulam, Thomas Moreau.
  • NeuMiss networks: differential programming for supervised learning with missing values. Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux.
  • Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso. Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon, Bertrand Thirion.

Congratulations to all !

3 papers accepted for AISTATS 2020

We are pleased to share the good news that three papers from our team have been accepted for AISTATS 2020 (International Conference on Artificial Intelligence and Statistics):

Debiased Sinkhorn barycenters
Hicham Janati (Inria and CREST/ENSAE), Marco Cuturi (Google and CREST/ENSAE), Alexandre Gramfort (Inria)

Support recovery and sup-norm convergence rates for sparse pivotal estimation

Mathurin Massias (Inria), Quentin Bertrand (Inria), Alexandre Gramfort (Inria), Joseph Salmon (Université de Montpellier)

Linear predictor on linearly-generated data with missing values: non consistency and solutions
Marine Le Morvan (CNRS), Nicolas Prost (CMAP), Julie Josse (Polytechnique/Inria), Erwan Scornet (École Polytechnique), Gael Varoquaux (Inria)

Kamalaker’s defense on September 14th

Kamalaker Dadi is defending his PhD thesis “Population Imaging for Mental Health” on Sept 14th in Alan Turing (and online !)

Here are the committee members:

  • Sylvia Villeneuve, McGill University, Canada
  • Pierre Bellec, Université de Montréal, Canada
  • Camille Maumet, Université Rennes I, France
  • Vincent Frouin, CEA Neurospin, Université Paris-Saclay, France
  • Michel Thiebaut, Université de Bordeaux, France
  • Gaël Varoquaux, Parietal Inria, Université Paris-Saclay, France
  • Bertrand Thirion, Parietal Inria, Université Paris-Saclay, France
  • Denis Engemann, Parietal Inria, Université Paris-Saclay, France
  • Josselin Houenou, UNIACT Lab, Université Paris-Saclay, France

Please join us to discover his great contributions to the field !

4 papers accepted for ICML 2020

We are pleased to share the good news that four papers from our team have been accepted for ICML 2020 (International Conference in Machine Learning):

Debiased Sinkhorn barycenters
Hicham Janati (Inria and CREST/ENSAE), Marco Cuturi (Google and CREST/ENSAE), Alexandre Gramfort (Inria)

Implicit differentiation of Lasso-type models for hyperparameter optimization
Quentin Bertrand (Inria), Quentin Klopfenstein (Université de Bourgogne), Mathieu Blondel (NTT), Samuel Vaiter (CNRS), Alexandre Gramfort (Inria), Joseph Salmon (Université de Montpellier)

Aggregation of Multiple Knockoffs
Tuan-Binh Nguyen (Inria), Jerome-Alexis Chevalier (Inria), Sylvain Arlot (University Paris Sud), Thirion Bertrand (Inria)

Super-efficiency of automatic differentiation for functions defined as a minimum
Pierre Ablin (CNRS and ENS), Gabriel Peyré (CNRS and ENS), Thomas Moreau (Inria)

New Article in Nature Communications! Collaboration with the Stanford Cognitive & Systems Neuroscience Lab

Are brain structures of written word decoding and attention linked? Can we predict cognitive performance?

Find out in our article in Nature Communications.


While predominant models of visual word form area (VWFA) function argue for its specific role in decoding written language, other accounts propose a more general role of VWFA in complex visual processing. However, a comprehensive examination of structural and functional VWFA circuits and their relationship to behavior has been missing. Here, using high-resolution multimodal imaging data from a large Human Connectome Project cohort (N = 313), we demonstrate robust patterns of VWFA connectivity with both canonical language and attentional networks. Brain-behavior relationships revealed a striking pattern of double dissociation: structural connectivity of VWFA with lateral temporal language network predicted language, but not visuo-spatial attention abilities, while VWFA connectivity with dorsal fronto-parietal attention network predicted visuo-spatial attention, but not language abilities. Our findings support a multiplex model of VWFA function characterized by distinct circuits for integrating language and attention, and point to connectivity-constrained cognition as a key principle of human brain organization.