( en | de | ru )

 

Disambiguation of "Thirion, Bertrand"

Author of the publication

copydeleteadd this publication to your clipboard
Triangulating cortical functional networks with anatomical landmarks.

, , , , and . ISBI, page 612-615. IEEE, (2008)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Bertrand Thirion

Christian Thirion

Bertrand Hirl

Bertrand Gloddek

Joachim Bertrand

 

Other publications of authors with the same name

Probabilistic Anatomo-Functional Parcellation of the Cortex: How Many Regions?., , , , , and . MICCAI (2), volume 5242 of Lecture Notes in Computer Science, page 399-406. Springer, (2008)Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates., , , , and . IPMI, volume 11492 of Lecture Notes in Computer Science, page 743-754. Springer, (2019)Multivariate Analysis is Sufficient for Lesion-Behaviour Mapping., , and . BrainLes@MICCAI (1), volume 12658 of Lecture Notes in Computer Science, page 92-100. Springer, (2020)Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps., , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 17499-17516. PMLR, (2022)Aggregation of Multiple Knockoffs., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 7283-7293. PMLR, (2020)Triangulating cortical functional networks with anatomical landmarks., , , , and . ISBI, page 612-615. IEEE, (2008)Parcellation Schemes and Statistical Tests to Detect Active Regions on the Cortical Surface., , and . COMPSTAT, page 565-572. Physica-Verlag, (2010)A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension., , and . NeurIPS, (2022)Aligning individual brains with fused unbalanced Gromov Wasserstein., , , , , , and . NeurIPS, (2022)Information-Restricted Neural Language Models Reveal Different Brain Regions' Sensitivity to Semantics, Syntax and Context., , , and . CoRR, (2023)