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• 2025
• 
  [j12]
  Tomás A. D'Amelio,Lorenzo Ariel Galán,Emmanuel Alesandro Maldonado,Agustín Ariel Díaz Barquinero,Jerónimo Rodríguez Cuello,Nicolás M. Bruno,Enzo Tagliazucchi,Denis-Alexander Engemann:
  Emotion recognition systems with electrodermal activity: From affective science to affective computing.Neurocomputing651:130831 (2025)
• 
  [j11]
  Joseph Paillard,Jörg F. Hipp,Denis A. Engemann:
  GREEN: A lightweight architecture using learnable wavelets and Riemannian geometry for biomarker exploration with EEG signals.Patterns6(3):101182 (2025)
• 
  [c11]
  Joseph Paillard,Angel David Reyero Lobo,Vitaliy Kolodyazhniy,Bertrand Thirion,Denis-Alexander Engemann:
  Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence.ICML2025
• 
  [c10]
  Joseph Paillard,Antoine Collas,Denis A. Engemann,Bertrand Thirion:
  Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction.IPMI (2)2025:79-93
• 
  [i11]
  Joseph Paillard,Antoine Collas,Denis A. Engemann,Bertrand Thirion:
  Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction.CoRRabs/2508.08724 (2025)
• 2024
• 
  [c9]
  Ahmad Chamma,Bertrand Thirion,Denis A. Engemann:
  Variable Importance in High-Dimensional Settings Requires Grouping.AAAI2024:11195-11203
• 
  [c8]
  Apolline Mellot,Antoine Collas,Sylvain Chevallier,Denis A. Engemann,Alexandre Gramfort:
  Physics-Informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets.EUSIPCO2024:1367-1371
• 
  [c7]
  Apolline Mellot,Antoine Collas,Sylvain Chevallier,Alexandre Gramfort,Denis A. Engemann:
  Geodesic Optimization for Predictive Shift Adaptation on EEG data.NeurIPS2024
• 
  [d5]
  Stefan Appelhoff,Matthew Sanderson,Teon L. Brooks,Marijn van Vliet,Romain Quentin,Chris Holdgraf,Maximilien Chaumon,Ezequiel Mikulan,Kambiz Tavabi,Richard Höchenberger,Dominik Welke,Clemens Brunner,Alexander Rockhill,Eric Larson,Adam Li,Ariel Rokem,Daniel McCloy,Austin J. Hurst,Diego Lozano-Soldevilla,Eduard Ort,Ethan Knights,Evgenii Kalenkovich,Franziska von Albedyll,Fu-Te Wong,Jean-Rémi King,Guiomar Niso,Richard Koehler,Robert Luke,Simon Kern,Sin Kim,Sophie Herbst,Swastika Gupta,Thomas Donoghue,Yorguin José Mantilla Ramos,Scott Huberty,Mathieu Scheltienne,Anand Saini,Bruno Hebling Vieira,Denis A. Engemann,Moritz Gerster,Laetitia Fesselier,Jonathan Vanhoecke,Ford McDonald,Pierre Guetschel,Mara Wolter,Julius Welzel,Alexandre Gramfort,Mainak Jas:
  MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Version v0.15.0.Zenodo,2024[all versions] 
• 
  [d4]
  Stefan Appelhoff,Matthew Sanderson,Teon L. Brooks,Marijn van Vliet,Romain Quentin,Chris Holdgraf,Maximilien Chaumon,Ezequiel Mikulan,Kambiz Tavabi,Richard Höchenberger,Dominik Welke,Clemens Brunner,Alexander Rockhill,Eric Larson,Adam Li,Ariel Rokem,Daniel McCloy,Austin J. Hurst,Diego Lozano-Soldevilla,Eduard Ort,Ethan Knights,Evgenii Kalenkovich,Franziska von Albedyll,Fu-Te Wong,Jean-Rémi King,Julia Guiomar Niso Galán,Richard M. Köhler,Robert Luke,Simon Kern,Sin Kim,Sophie Herbst,Swastika Gupta,Thomas Donoghue,Yorguin José Mantilla Ramos,Scott Huberty,Mathieu Scheltienne,Anand Saini,Bruno Hebling Vieira,Denis A. Engemann,Moritz Gerster,Laetitia Fesselier,Jonathan Vanhoecke,Ford McDonald,Pierre Guetschel,Mara Wolter,Julius Welzel,Kaare B. Mikkelsen,Amaia Benitez Andonegui,Thomas Hartmann,Aaron Earle-Richardson,William F. Turner,Alexandre Gramfort,Mainak Jas:
  MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Version v0.16.0.Zenodo,2024[all versions] 
• 
  [i10]
  Apolline Mellot,Antoine Collas,Sylvain Chevallier,Denis A. Engemann,Alexandre Gramfort:
  Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets.CoRRabs/2403.15415 (2024)
• 
  [i9]
  Apolline Mellot,Antoine Collas,Sylvain Chevallier,Alexandre Gramfort,Denis A. Engemann:
  Geodesic Optimization for Predictive Shift Adaptation on EEG data.CoRRabs/2407.03878 (2024)
• 
  [i8]
  Joseph Paillard,Vitaliy Kolodyazhniy,Bertrand Thirion,Denis A. Engemann:
  Measuring Variable Importance in Individual Treatment Effect Estimation with High Dimensional Data.CoRRabs/2408.13002 (2024)
• 2023
• 
  [j10]
  Robert J. Jirsaraie,Aaron J. Gorelik,Martins M. Gatavins,Denis A. Engemann,Ryan Bogdan,Deanna M. Barch,Aristeidis Sotiras:
  A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility.Patterns4(4):100712 (2023)
• 
  [c6]
  Ahmad Chamma,Denis A. Engemann,Bertrand Thirion:
  Statistically Valid Variable Importance Assessment through Conditional Permutations.NeurIPS2023
• 
  [i7]
  Ahmad Chamma,Denis A. Engemann,Bertrand Thirion:
  Statistically Valid Variable Importance Assessment through Conditional Permutations.CoRRabs/2309.07593 (2023)
• 
  [i6]
  Ahmad Chamma,Bertrand Thirion,Denis A. Engemann:
  Variable Importance in High-Dimensional Settings Requires Grouping.CoRRabs/2312.10858 (2023)
• 2022
• 
  [j9]
  Hubert J. Banville,Sean U. N. Wood,Chris Aimone,Denis-Alexander Engemann,Alexandre Gramfort:
  Robust learning from corrupted EEG with dynamic spatial filtering.NeuroImage251:118994 (2022)
• 
  [j8]
  Denis A. Engemann,Apolline Mellot,Richard Höchenberger,Hubert J. Banville,David Sabbagh,Lukas Gemein,Tonio Ball,Alexandre Gramfort:
  A reusable benchmark of brain-age prediction from M/EEG resting-state signals.NeuroImage262:119521 (2022)
• 
  [d3]
  Stefan Appelhoff,Matthew Sanderson,Teon L. Brooks,Marijn van Vliet,Romain Quentin,Chris Holdgraf,Maximilien Chaumon,Ezequiel Mikulan,Kambiz Tavabi,Richard Höchenberger,Dominik Welke,Clemens Brunner,Alexander Rockhill,Eric Larson,Adam Li,Ariel Rokem,Daniel McCloy,Austin J. Hurst,Diego Lozano-Soldevilla,Eduard Ort,Ethan Knights,Evgenii Kalenkovich,Franziska von Albedyll,Fu-Te Wong,Jean-Rémi King,Julia Guiomar Niso Galán,Richard Koehler,Robert Luke,Simon Kern,Sin Kim,Sophie Herbst,Swastika Gupta,Thomas Donoghue,Yorguin José Mantilla Ramos,Scott Huberty,Mathieu Scheltienne,Anand Saini,Bruno Hebling Vieira,Denis A. Engemann,Alexandre Gramfort,Mainak Jas:
  MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Version v0.11.Zenodo,2022[all versions] 
• 
  [d2]
  Stefan Appelhoff,Matthew Sanderson,Teon L. Brooks,Marijn van Vliet,Romain Quentin,Chris Holdgraf,Maximilien Chaumon,Ezequiel Mikulan,Kambiz Tavabi,Richard Höchenberger,Dominik Welke,Clemens Brunner,Alexander Rockhill,Eric Larson,Adam Li,Ariel Rokem,Daniel McCloy,Austin J. Hurst,Diego Lozano-Soldevilla,Eduard Ort,Ethan Knights,Evgenii Kalenkovich,Franziska von Albedyll,Fu-Te Wong,Jean-Rémi King,J. Guiomar Niso,Richard Koehler,Robert Luke,Simon Kern,Sin Kim,Sophie Herbst,Swastika Gupta,Thomas Donoghue,Yorguin José Mantilla Ramos,Scott Huberty,Mathieu Scheltienne,Anand Saini,Bruno Hebling Vieira,Denis A. Engemann,Alexandre Gramfort,Mainak Jas:
  MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Version v0.11.1.Zenodo,2022[all versions] 
• 
  [d1]
  Stefan Appelhoff,Matthew Sanderson,Teon L. Brooks,Marijn van Vliet,Romain Quentin,Chris Holdgraf,Maximilien Chaumon,Ezequiel Mikulan,Kambiz Tavabi,Richard Höchenberger,Dominik Welke,Clemens Brunner,Alexander Rockhill,Eric Larson,Adam Li,Ariel Rokem,Daniel McCloy,Austin J. Hurst,Diego Lozano-Soldevilla,Eduard Ort,Ethan Knights,Evgenii Kalenkovich,Franziska von Albedyll,Fu-Te Wong,Jean-Rémi King,J. Guiomar Niso,Richard Koehler,Robert Luke,Simon Kern,Sin Kim,Sophie Herbst,Swastika Gupta,Thomas Donoghue,Yorguin José Mantilla Ramos,Scott Huberty,Mathieu Scheltienne,Anand Saini,Bruno Hebling Vieira,Denis A. Engemann,Moritz Gerster,Alexandre Gramfort,Mainak Jas:
  MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Version v0.12.Zenodo,2022[all versions] 
• 2021
• 
  [c5]
  Alexandre Gramfort,Hubert J. Banville,Omar Chehab,Aapo Hyvärinen,Denis A. Engemann:
  Learning with self-supervision on EEG data.BCI2021:1-2
• 
  [i5]
  Hubert J. Banville,Sean U. N. Wood,Chris Aimone,Denis-Alexander Engemann,Alexandre Gramfort:
  Robust learning from corrupted EEG with dynamic spatial filtering.CoRRabs/2105.12916 (2021)
• 2020
• 
  [j7]
  Daria La Rocca,Philippe Ciuciu,Denis-Alexander Engemann,Virginie van Wassenhove:
  Emergence ofβ andγ networks following multisensory training.NeuroImage206 (2020)
• 
  [j6]
  David Sabbagh,Pierre Ablin,Gaël Varoquaux,Alexandre Gramfort,Denis A. Engemann:
  Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.NeuroImage222:116893 (2020)
• 
  [j5]
  Danilo Bzdok,Denis A. Engemann,Bertrand Thirion:
  Inference and Prediction Diverge in Biomedicine.Patterns1(8):100119 (2020)
• 
  [i4]
  Hubert J. Banville,Omar Chehab,Aapo Hyvärinen,Denis-Alexander Engemann,Alexandre Gramfort:
  Uncovering the structure of clinical EEG signals with self-supervised learning.CoRRabs/2007.16104 (2020)

• 2019
• 
  [c4]
  Hubert J. Banville,Graeme Moffat,Isabela Albuquerque,Denis-Alexander Engemann,Aapo Hyvärinen,Alexandre Gramfort:
  Self-Supervised Representation Learning from Electroencephalography Signals.MLSP2019:1-6
• 
  [c3]
  David Sabbagh,Pierre Ablin,Gaël Varoquaux,Alexandre Gramfort,Denis A. Engemann:
  Manifold-regression to predict from MEG/EEG brain signals without source modeling.NeurIPS2019:7321-7332
• 
  [i3]
  David Sabbagh,Pierre Ablin,Gaël Varoquaux,Alexandre Gramfort,Denis A. Engemann:
  Manifold-regression to predict from MEG/EEG brain signals without source modeling.CoRRabs/1906.02687 (2019)
• 
  [i2]
  Hubert J. Banville,Isabela Albuquerque,Aapo Hyvärinen,Graeme Moffat,Denis-Alexander Engemann,Alexandre Gramfort:
  Self-supervised representation learning from electroencephalography signals.CoRRabs/1911.05419 (2019)
• 2017
• 
  [j4]
  Gaël Varoquaux,Pradeep Reddy Raamana,Denis A. Engemann,Andrés Hoyos Idrobo,Yannick Schwartz,Bertrand Thirion:
  Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines.NeuroImage145:166-179 (2017)
• 
  [j3]
  Mainak Jas,Denis A. Engemann,Yousra Bekhti,Federico Raimondo,Alexandre Gramfort:
  Autoreject: Automated artifact rejection for MEG and EEG data.NeuroImage159:417-429 (2017)
• 2016
• 
  [c2]
  Mainak Jas,Denis A. Engemann,Federico Raimondo,Yousra Bekhti,Alexandre Gramfort:
  Automated rejection and repair of bad trials in MEG/EEG.PRNI2016:1-4
• 2015
• 
  [b1]
  Denis A. Engemann:
  Neuromagnetic Decomposition of Social Interaction. University of Cologne,2015
• 
  [j2]
  Denis A. Engemann,Alexandre Gramfort:
  Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.NeuroImage108:328-342 (2015)
• 
  [c1]
  Denis A. Engemann,Daniel Strohmeier,Eric Larson,Alexandre Gramfort:
  Mind the Noise Covariance When Localizing Brain Sources with M/EEG.PRNI2015:9-12
• 
  [i1]
  Carl-Friedrich Schleussner,Jonathan F. Donges,Denis A. Engemann,Anders Levermann:
  Co-evolutionary behaviour selection in adaptive social networks predicts clustered marginalization of minorities.CoRRabs/1512.05013 (2015)
• 2014
• 
  [j1]
  Alexandre Gramfort,Martin Luessi,Eric Larson,Denis A. Engemann,Daniel Strohmeier,Christian Brodbeck,Lauri Parkkonen,Matti S. Hämäläinen:
  MNE software for processing MEG and EEG data.NeuroImage86:446-460 (2014)

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