Denis A. Engemann

According to our database, Denis A. Engemann authored at least 21 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets.

Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort

CoRR, 2024

Variable Importance in High-Dimensional Settings Requires Grouping.

Ahmad Chamma, Bertrand Thirion, Denis A. Engemann

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility.

Robert J. Jirsaraie, Aaron J. Gorelik, Martins M. Gatavins, Denis A. Engemann, Ryan Bogdan, Deanna M. Barch, Aristeidis Sotiras

Patterns, April, 2023

Statistically Valid Variable Importance Assessment through Conditional Permutations.

Ahmad Chamma, Denis A. Engemann, Bertrand Thirion

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A reusable benchmark of brain-age prediction from M/EEG resting-state signals.

Denis A. Engemann, Apolline Mellot, Richard Höchenberger, Hubert J. Banville, David Sabbagh, Lukas Gemein, Tonio Ball, Alexandre Gramfort

NeuroImage, 2022

Robust learning from corrupted EEG with dynamic spatial filtering.

Hubert J. Banville, Sean U. N. Wood, Chris Aimone, Denis-Alexander Engemann, Alexandre Gramfort

NeuroImage, 2022

2021

Learning with self-supervision on EEG data.

Alexandre Gramfort, Hubert J. Banville, Omar Chehab, Aapo Hyvärinen, Denis A. Engemann

Proceedings of the 9th International Winter Conference on Brain-Computer Interface, 2021

2020

Inference and Prediction Diverge in Biomedicine.

Danilo Bzdok, Denis A. Engemann, Bertrand Thirion

Patterns, 2020

Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.

David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann

NeuroImage, 2020

Emergence of <i>β</i> and <i>γ</i> networks following multisensory training.

Daria La Rocca, Philippe Ciuciu, Denis-Alexander Engemann, Virginie van Wassenhove

NeuroImage, 2020

Uncovering the structure of clinical EEG signals with self-supervised learning.

Hubert J. Banville, Omar Chehab, Aapo Hyvärinen, Denis-Alexander Engemann, Alexandre Gramfort

CoRR, 2020

2019

Manifold-regression to predict from MEG/EEG brain signals without source modeling.

David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Self-Supervised Representation Learning from Electroencephalography Signals.

Hubert J. Banville, Graeme Moffat, Isabela Albuquerque, Denis-Alexander Engemann, Aapo Hyvärinen, Alexandre Gramfort

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

2017

Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines.

Gaël Varoquaux, Pradeep Reddy Raamana, Denis A. Engemann, Andrés Hoyos Idrobo, Yannick Schwartz, Bertrand Thirion

NeuroImage, 2017

Autoreject: Automated artifact rejection for MEG and EEG data.

Mainak Jas, Denis A. Engemann, Yousra Bekhti, Federico Raimondo, Alexandre Gramfort

NeuroImage, 2017

2016

Automated rejection and repair of bad trials in MEG/EEG.

Mainak Jas, Denis A. Engemann, Federico Raimondo, Yousra Bekhti, Alexandre Gramfort

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

2015

Neuromagnetic Decomposition of Social Interaction.

Denis A. Engemann

PhD thesis, 2015

Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

Denis A. Engemann, Alexandre Gramfort

NeuroImage, 2015

Co-evolutionary behaviour selection in adaptive social networks predicts clustered marginalization of minorities.

Carl-Friedrich Schleussner, Jonathan F. Donges, Denis A. Engemann, Anders Levermann

CoRR, 2015

Mind the Noise Covariance When Localizing Brain Sources with M/EEG.

Denis A. Engemann, Daniel Strohmeier, Eric Larson, Alexandre Gramfort

Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

2014

MNE software for processing MEG and EEG data.

Alexandre Gramfort, Martin Luessi, Eric Larson, Denis A. Engemann, Daniel Strohmeier, Christian Brodbeck, Lauri Parkkonen, Matti S. Hämäläinen

NeuroImage, 2014