Importance des variables dans les méthodes CART. - Badih Ghattas (Monde des Util. Anal. Données, 1999)

Procédure manuelle pour la construction d'arbres de régression sous S+. - Badih Ghattas (Monde des Util. Anal. Données, 1999)

Classifying densities using functional regression trees: Applications in oceanology. - David Nerini; Badih Ghattas (Comput. Stat. Data Anal., 2007)

Interpretable clustering using unsupervised binary trees. - Ricardo Fraiman; Badih Ghattas; Marcela Svarc (Adv. Data Anal. Classif., 2013)

Random average shifted histograms. - Mathias Bourel; Ricardo Fraiman; Badih Ghattas (Comput. Stat. Data Anal., 2014)

Bayesian Network Classification: Application to Epilepsy Type Prediction Using PET Scan Data. - Kamel Jebreen; Badih Ghattas (ICMLA, 2016)

Direct Multiclass Boosting Using Base Classifiers' Posterior Probabilities Estimates. - Mathias Bourel; Badih Ghattas (ICMLA, 2017)

Clustering nominal data using unsupervised binary decision trees: Comparisons with the state of the art methods. - Badih Ghattas; Pierre Michel; Laurent Boyer (Pattern Recognit., 2017)

Inferring linear and nonlinear Interaction networks using neighborhood support vector machines. - Kamel Jebreen; Badih Ghattas (CoRR, 2019)

Textual Data for Time Series Forecasting. - David Obst; Badih Ghattas; Sandra Claudel; Jairo Cugliari; Yannig Goude; Georges Oppenheim (CoRR, 2019)

Assessing variable importance in clustering: a new method based on unsupervised binary decision trees. - Badih Ghattas; Pierre Michel; Laurent Boyer (Comput. Stat., 2019)

Multivariate and functional robust fusion methods for structured Big Data. - Catherine Aaron; Alejandro Cholaquidis; Ricardo Fraiman; Badih Ghattas (J. Multivar. Anal., 2019)

OLOGRAM: determining significance of total overlap length between genomic regions sets. - Quentin Ferré; Guillaume Charbonnier; N. Sadouni; Frédéric Lopez; Yasmina Kermezli; Salvatore Spicuglia; Cécile Capponi; Badih Ghattas; Denis Puthier (Bioinform., 2020)

Deep Learning for Semantic Segmentation. - Alexandre Benoît; Badih Ghattas; Emna Amri; Joris Fournel; Patrick Lambert (Multi-faceted Deep Learning, 2021)

MapReduce Clustering for Big Data. - Badih Ghattas; Antoine Pinto; Sambou Diao (IEEE BigData, 2021)

Transfer Learning for Linear Regression: a Statistical Test of Gain. - David Obst; Badih Ghattas; Jairo Cugliari; Georges Oppenheim; Sandra Claudel; Yannig Goude (CoRR, 2021)

Medical image segmentation automatic quality control: A multi-dimensional approach. - Joris Fournel; Axel Bartoli; David Bendahan; Maxime Guye; Monique Bernard; Elisa Rauseo; Mohammed Y. Khanji; Steffen E. Petersen; Alexis Jacquier; Badih Ghattas (Medical Image Anal., 2021)

Improved linear regression prediction by transfer learning. - David Obst; Badih Ghattas; Sandra Claudel; Jairo Cugliari; Yannig Goude; Georges Oppenheim (Comput. Stat. Data Anal., 2022)

FDG-PET to T1 Weighted MRI Translation with 3D Elicit Generative Adversarial Network (E-GAN). - Farideh Bazangani; Frédéric J. P. Richard; Badih Ghattas; Eric Guedj (Sensors, 2022)

Subsampling under distributional constraints. - Florian Combes; Ricardo Fraiman; Badih Ghattas (Stat. Anal. Data Min., 2024)

Textual data for electricity load forecasting. - David Obst; Sandra Claudel; Jairo Cugliari; Badih Ghattas; Yannig Goude; Georges Oppenheim (Qual. Reliab. Eng. Int., 2024)

Enhanced Vascular Flow Simulations in Aortic Aneurysm via Physics-Informed Neural Networks and Deep Operator Networks. - Oscar L. Cruz-González; Valérie Deplano; Badih Ghattas (CoRR, 2025)