A Study of Image Compression with Backpropagation. - Mathilde Mougeot; Robert Azencott; Bernard Angéniol (NATO Neurocomputing, 1989)

Image compression with back propagation: Improvement of the visual restoration using different cost functions. - Mathilde Mougeot; Robert Azencott; Bernard Angéniol (Neural Networks, 1991)

Sparse Approximation and Fit of Intraday Load Curves in a High Dimensional Framework. - Mathilde Mougeot; Dominique Picard; Karine Tribouley; Vincent Lefieux; Laurence Maillard-Teyssier (Adv. Data Sci. Adapt. Anal., 2013)

LOL selection in high dimension. - Mathilde Mougeot; Dominique Picard; Karine Tribouley (Comput. Stat. Data Anal., 2014)

anomaly detection on spectrograms using data-driven and fixed dictionary representations. - Mina Abdel-Sayed; Daniel Duclos; Gilles Faÿ; Jérôme Lacaille; Mathilde Mougeot (ESANN, 2016)

Dictionary Comparison for Anomaly Detection on Aircraft Engine Spectrograms. - Mina Abdel-Sayed; Daniel Duclos; Gilles Faÿ; Jérôme Lacaille; Mathilde Mougeot (MLDM, 2016)

Fall detection using smart floor sensor and supervised learning. - Ludovic Minvielle; Mounir Atiq; Renan Serra; Mathilde Mougeot; Nicolas Vayatis (EMBC, 2017)

Transfer Learning on Decision Tree with Class Imbalance. - Ludovic Minvielle; Mounir Atiq; Sergio Peignier; Mathilde Mougeot (ICTAI, 2019)

Unsupervised Multi-source Domain Adaptation for Regression. - Guillaume Richard; Antoine de Mathelin; Georges Hébrail; Mathilde Mougeot; Nicolas Vayatis (ECML/PKDD (1), 2020)

Predicting Job Power Consumption Based on RJMS Submission Data in HPC Systems. - Théo Saillant; Jean-Christophe Weill; Mathilde Mougeot (ISC, 2020)

Adversarial Weighting for Domain Adaptation in Regression. - Antoine de Mathelin; Guillaume Richard; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2020)

Model family selection for classification using Neural Decision Trees. - Anthea Mérida Montes de Oca; Argyris Kalogeratos; Mathilde Mougeot (CoRR, 2020)

Leveraging Digital Disruptions for a Climate-Safe and Equitable World: The D^2S Agenda: [Commentary]. - Amy Luers; Jennifer Garard; Asun Lera St. Clair; Owen Gaffney; Tom Hassenboehler; Lyse Langlois; Mathilde Mougeot; Sasha Luccioni (IEEE Technol. Soc. Mag., 2020)

Sustainability in the Digital Age [Special Issue Introduction]. - Amy Luers; Lyse Langlois; Mathilde Mougeot; Sana Kharaghani; Alexandra Luccioni (IEEE Technol. Soc. Mag., 2020)

Bayesian Feature Discovery for Predictive Maintenance. - Amir Dib; Charles Truong; Laurent Oudre; Mathilde Mougeot; Nicolas Vayatis; Heloïse Nonne (EUSIPCO, 2021)

Constrained prediction time random forests using equivalent trees and genetic programming: application to fall detection model embedding. - Mounir Atiq; Sergio Peignier; Mathilde Mougeot (ICTAI, 2021)

Adversarial Weighting for Domain Adaptation in Regression. - Antoine de Mathelin; Guillaume Richard; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (ICTAI, 2021)

Discrepancy-Based Active Learning for Domain Adaptation. - Antoine de Mathelin; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2021)

ADAPT : Awesome Domain Adaptation Python Toolbox. - Antoine de Mathelin; François Deheeger; Guillaume Richard; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2021)

A Binded VAE for Inorganic Material Generation. - Fouad Oubari; Antoine de Mathelin; Rodrigue Décatoire; Mathilde Mougeot (CoRR, 2021)

To Tree or Not to Tree? Assessing the Impact of Smoothing the Decision Boundaries. - Anthea Mérida; Argyris Kalogeratos; Mathilde Mougeot (ICANN (1), 2022)

Discrepancy-Based Active Learning for Domain Adaptation. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (ICLR, 2022)

Fast and Accurate Importance Weighting for Correcting Sample Bias. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (ECML/PKDD (1), 2022)

Fixed-budget online adaptive mesh learning for physics-informed neural networks. Towards parameterized problem inference. - Thi Nguyen Khoa Nguyen; Thibault Dairay; Raphaël Meunier; Christophe Millet; Mathilde Mougeot (CoRR, 2022)

Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: An application to rubber calendering process. - Thi Nguyen Khoa Nguyen; Thibault Dairay; Raphaël Meunier; Mathilde Mougeot (Eng. Appl. Artif. Intell., 2022)

Fixed-Budget Online Adaptive Learning for Physics-Informed Neural Networks. Towards Parameterized Problem Inference. - Thi Nguyen Khoa Nguyen; Thibault Dairay; Raphaël Meunier; Christophe Millet; Mathilde Mougeot (ICCS (4), 2023)

Personalized One-Shot Collaborative Learning. - Marie Garin; Antoine de Mathelin; Mathilde Mougeot; Nicolas Vayatis (ICTAI, 2023)

Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2023)

A Meta-Generation framework for Industrial System Generation. - Fouad Oubari; Raphaël Meunier; Rodrigue Décatoire; Mathilde Mougeot (CoRR, 2023)

Maximum Weight Entropy. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2023)

A Data Set for Fall Detection with Smart Floor Sensors. - Charles Truong; Mounir Atiq; Ludovic Minvielle; Renan Serra; Mathilde Mougeot; Nicolas Vayatis (Image Process. Line, 2023)

Contrastive Learning: An Efficient Domain Adaptation Strategy for 2D Mammography Image Classification. - Gonzalo Iñaki Quintana; Vincent Jugnon; Laurence Vancamberg; Agnès Desolneux; Mathilde Mougeot (ISBI, 2024)

A Meta-VAE for Multi-component Industrial Systems Generation. - Fouad Oubari; Raphaël Meunier; Rodrigue Décatoire; Mathilde Mougeot (SAI (1), 2024)

Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees. - Edgar Jaber; Vincent Blot; Nicolas J.-B. Brunel; Vincent Chabridon; Emmanuel Remy; Bertrand Iooss; Didier Lucor; Mathilde Mougeot; Alessandro Leite (CoRR, 2024)

Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials. - Thi Nguyen Khoa Nguyen; Thibault Dairay; Raphaël Meunier; Christophe Millet; Mathilde Mougeot (CoRR, 2024)

A Markov Random Field Multi-Modal Variational AutoEncoder. - Fouad Oubari; Mohamed El Baha; Raphaël Meunier; Rodrigue Décatoire; Mathilde Mougeot (CoRR, 2024)

BN-SCAFFOLD: controlling the drift of Batch Normalization statistics in Federated Learning. - Gonzalo Iñaki Quintana; Laurence Vancamberg; Vincent Jugnon; Mathilde Mougeot; Agnès Desolneux (CoRR, 2024)

OneBatchPAM: A Fast and Frugal K-Medoids Algorithm. - Antoine de Mathelin; Nicolas Enrique Cecchi; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (AAAI, 2025)

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials. - Thi Nguyen Khoa Nguyen; Thibault Dairay; Raphaël Meunier; Jean Di Stasio; Christophe Millet; Mathilde Mougeot (Comput. Phys. Commun., 2025)

Bridging Contrastive Learning and Domain Adaptation: Theoretical Perspective and Practical Application. - Gonzalo Iñaki Quintana; Laurence Vancamberg; Vincent Jugnon; Agnès Desolneux; Mathilde Mougeot (CoRR, 2025)

Deep Generative Methods and Tire Architecture Design. - Fouad Oubari; Raphaël Meunier; Rodrigue Décatoire; Mathilde Mougeot (CoRR, 2025)

Multi-Component VAE with Gaussian Markov Random Field. - Fouad Oubari; Mohamed El Baha; Raphaël Meunier; Rodrigue Décatoire; Mathilde Mougeot (CoRR, 2025)