Assessing the segmentation performance of pairwise and triplet Markov models. - Ivan Gorynin; Hugo Gangloff; Emmanuel Monfrini; Wojciech Pieczynski (Signal Process., 2018)

Unsupervised segmentation of stents corrupted by artifacts in medical X-ray images. - Hugo Gangloff; Emmanuel Monfrini; Christophe Collet 001; Nabil Chakfé (IPTA, 2020)

Improved centerline tracking for new descriptors of atherosclerotic aortas. - Hugo Gangloff; Emmanuel Monfrini; Mohamed Zied Ghariani; Mickaël Ohana; Christophe Collet 001; Nabil Chakfé (IPTA, 2020)

Probabilistic models for image processing: applications in vascular surgery. (Modèles probabilistes pour le traitement d'image: application à la chirurgie vasculaire). - Hugo Gangloff (2020)

Unsupervised Image Segmentation with Spatial Triplet Markov Trees. - Hugo Gangloff; Jean-Baptiste Courbot; Emmanuel Monfrini; Christophe Collet 001 (ICASSP, 2021)

A General Parametrization Framework for Pairwise Markov Models: An Application to Unsupervised Image Segmentation. - Hugo Gangloff; Katherine Morales; Yohan Petetin (MLSP, 2021)

Unsupervised image segmentation with Gaussian Pairwise Markov Fields. - Hugo Gangloff; Jean-Baptiste Courbot; Emmanuel Monfrini; Christophe Collet 001 (Comput. Stat. Data Anal., 2021)

Leveraging Vector-Quantized Variational Autoencoder Inner Metrics for Anomaly Detection. - Hugo Gangloff; Minh-Tan Pham; Luc Courtrai; Sébastien Lefèvre (ICPR, 2022)

Unsupervised Anomaly Detection Using Variational Autoencoder with Gaussian Random Field Prior. - Hugo Gangloff; Minh-Tan Pham; Luc Courtrai; Sébastien Lefèvre (ICIP, 2023)

Variational Autoencoders for Unsupervised Object Counting from VHR Imagery: Applications in Dwelling Extraction from Forcibly Displaced People Settlement Areas. - Getachew Workineh Gella; Hugo Gangloff; Lorenz Wendt; Dirk Tiede; Stefan Lang 001 (IGARSS, 2023)

Weakly Supervised Marine Animal Detection from Remote Sensing Images Using Vector-Quantized Variational Autoencoder. - Minh-Tan Pham; Hugo Gangloff; Sébastien Lefèvre (IGARSS, 2023)

Object Counting from Aerial Remote Sensing Images: Application to Wildlife and Marine Mammals. - Tanya Singh; Hugo Gangloff; Minh-Tan Pham (IGARSS, 2023)

Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data. - Hugo Gangloff; Katherine Morales; Yohan Petetin (Comput. Stat. Data Anal., 2023)

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment. - Inass Soukarieh; Gerhard Hessler; Hervé Minoux; Marcel Mohr; K. Friedemann Schmidt; Jan Wenzel; Pierre Barbillon; Hugo Gangloff; Pierre Gloaguen (CoRR, 2024)

jinns: a JAX Library for Physics-Informed Neural Networks. - Hugo Gangloff; Nicolas Jouvin (CoRR, 2024)

Self-Supervised Variational Autoencoder for Unsupervised Object Counting from Very-High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas. - Getachew Workineh Gella; Hugo Gangloff; Lorenz Wendt; Dirk Tiede; Stefan Lang 001 (IEEE Trans. Geosci. Remote. Sens., 2024)

Leveraging Satellite Data With Machine and Deep Learning Techniques for Corn Yield and Price Forecasting. - Florian Teste; Hugo Gangloff; Mathilde Chen; Philippe Ciais; David Makowski (IEEE Trans. Geosci. Remote. Sens., 2024)

Gaussian Unit-simplex Markov random fields as a fast proxy for MRF sampling. - Jean-Baptiste Courbot; Hugo Gangloff (SSP, 2025)