Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. - Matthias Wilms; Jordan J. Bannister; Pauline Mouches; M. Ethan MacDonald; Deepthi Rajashekar; Sönke Langner; Nils D. Forkert (MLCN/RNO-AI@MICCAI, 2020)

Multi-institutional Travelling Model for Tumor Segmentation in MRI Datasets. - Raissa Souza; Anup Tuladhar; Pauline Mouches; Matthias Wilms; Lakshay Tyagi; Nils D. Forkert (BrainLes@MICCAI (2), 2021)

Towards Self-explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows. - Matthias Wilms; Pauline Mouches; Jordan J. Bannister; Deepthi Rajashekar; Sönke Langner; Nils D. Forkert (MLCN@MICCAI, 2021)

Unifying Brain Age Prediction and Age-Conditioned Template Generation with a Deterministic Autoencoder. - Pauline Mouches; Matthias Wilms; Deepthi Rajashekar; Sönke Langner; Nils Daniel Forkert (MIDL, 2021)

Detecting brain network communities: Considering the role of information flow and its different temporal scales. - Lazaro M. Sanchez-Rodriguez; Yasser Iturria-Medina; Pauline Mouches; Roberto C. Sotero (NeuroImage, 2021)

A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorder. - Emma A. M. Stanley; Deepthi Rajashekar; Pauline Mouches; Matthias Wilms; Kira Plettl; Nils D. Forkert (Computer-Aided Diagnosis, 2022)

Disentangling Factors of Morphological Variation in an Invertible Brain Aging Model. - Matthias Wilms; Pauline Mouches; Jordan J. Bannister; Sönke Langner; Nils D. Forkert (MAD@MICCAI, 2022)

An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction. - Raissa Souza; Pauline Mouches; Matthias Wilms; Anup Tuladhar; Sönke Langner; Nils D. Forkert (J. Am. Medical Informatics Assoc., 2022)

Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging. - Matthias Wilms; Jordan J. Bannister; Pauline Mouches; M. Ethan MacDonald; Deepthi Rajashekar; Sönke Langner; Nils D. Forkert (IEEE Trans. Medical Imaging, 2022)

Dementia in Convolutional Neural Networks: Using Deep Learning Models to Simulate Neurodegeneration of the Visual System. - Jasmine A. Moore; Anup Tuladhar; Zahinoor Ismail; Pauline Mouches; Matthias Wilms; Nils D. Forkert (Neuroinformatics, 2023)

Time CNN and Graph Convolution Network for Epileptic Spike Detection in Meg Data. - Pauline Mouches; Thibaut Dejean; Julien Jung; Romain Bouet; Carole Lartizien; Romain Quentin (ISBI, 2024)