Deep Sequence-to-Sequence Neural Networks for Ionospheric Activity Map Prediction. - Noëlie Cherrier; Thibaut Castaings; Alexandre Boulch (ICONIP (5), 2017)

Ionospheric activity prediction using convolutional recurrent neural networks. - Alexandre Boulch; Noëlie Cherrier; Thibaut Castaings (CoRR, 2018)

Consistent Feature Construction with Constrained Genetic Programming for Experimental Physics. - Noëlie Cherrier; Jean-Philippe Poli; Maxime Defurne; Franck Sabatié (CEC, 2019)

Embedded Constrained Feature Construction for High-Energy Physics Data Classification. - Noëlie Cherrier; Maxime Defurne; Jean-Philippe Poli; Franck Sabatié (CoRR, 2019)

Sim-to-Real Domain Adaptation For High Energy Physics. - Marouen Baalouch; Maxime Defurne; Jean-Philippe Poli; Noëlie Cherrier (CoRR, 2019)

Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction. - Noëlie Cherrier; Michael Mayo; Jean-Philippe Poli; Maxime Defurne; Franck Sabatié (DS, 2020)

Embedded Feature Construction in Fuzzy Decision Tree Induction for High Energy Physics Classification. - Noëlie Cherrier; Jean-Philippe Poli; Maxime Defurne; Franck Sabatié (SMC, 2020)

Interpretable machine learning for CLAS12 data analysis. (Machine learning interprétable pour l'analyse de données à CLAS12). - Noëlie Cherrier (2021)

A Bayesian Markov Model for Station-Level Origin-Destination Matrix Reconstruction. - Victor Amblard; Amir Dib; Noëlie Cherrier; Guillaume Barthe (ECML/PKDD (6), 2022)

Context-Aware Automated Passenger Counting Data Denoising. - Noëlie Cherrier; Baptiste Rérolle; Martin Graive; Amir Dib; Eglantine Schmitt (ITSC, 2023)

Unified Occupancy on a Public Transport Network Through Combination of AFC and APC Data. - Amir Dib; Noëlie Cherrier; Martin Graive; Baptiste Rérolle; Eglantine Schmitt (ITSC, 2023)