Shape metrics, warping and statistics. - Guillaume Charpiat; Olivier D. Faugeras; Renaud Keriven (ICIP (2), 2003)

Image Statistics Based on Diffeomorphic Matching. - Guillaume Charpiat; Olivier D. Faugeras; Renaud Keriven (ICCV, 2005)

Designing Spatially Coherent Minimizing Flows for Variational Problems Based on Active Contours. - Guillaume Charpiat; Renaud Keriven; Jean-Philippe Pons; Olivier D. Faugeras (ICCV, 2005)

Approximations of Shape Metrics and Application to Shape Warping and Empirical Shape Statistics. - Guillaume Charpiat; Olivier D. Faugeras; Renaud Keriven (Found. Comput. Math., 2005)

Approximations of Shape Metrics and Application to Shape Warping and Empirical Shape Statistics. - Guillaume Charpiat; Olivier D. Faugeras; Renaud Keriven; Pierre Maurel (Statistics and Analysis of Shapes, 2006)

Distance-Based Shape Statistics. - Guillaume Charpiat; Olivier D. Faugeras; Renaud Keriven; Pierre Maurel (ICASSP (5), 2006)

Distance-based shape statistics for image segmentation with priors. (Statistiques de formes pour la segmentation d'images avec a priori). - Guillaume Charpiat (2006)

Shape Statistics for Image Segmentation with Prior. - Guillaume Charpiat; Olivier D. Faugeras; Renaud Keriven (CVPR, 2007)

Generalized Gradients: Priors on Minimization Flows. - Guillaume Charpiat; Pierre Maurel; Jean-Philippe Pons; Renaud Keriven; Olivier D. Faugeras (Int. J. Comput. Vis., 2007)

Automatic Image Colorization Via Multimodal Predictions. - Guillaume Charpiat; Matthias Hofmann; Bernhard Schölkopf (ECCV (3), 2008)

Learning shape metrics based on deformations and transport. - Guillaume Charpiat (ICCV Workshops, 2009)

Converting Level Set Gradients to Shape Gradients. - Siqi Chen; Guillaume Charpiat; Richard J. Radke (ECCV (5), 2010)

Multiple Birth and Cut Algorithm for Multiple Object Detection. - Ahmed Gamal-Eldin; Xavier Descombes; Guillaume Charpiat; Josiane Zerubia (J. Multim. Process. Technol., 2010)

Exhaustive family of energies minimizable exactly by a graph cut. - Guillaume Charpiat (CVPR, 2011)

A fast Multiple Birth and Cut algorithm using belief propagation. - Ahmed Gamal-Eldin; Xavier Descombes; Guillaume Charpiat; Josiane Zerubia (ICIP, 2011)

A Cognitive Vision System for Nuclear Fusion Device Monitoring. - Vincent Martin 001; Victor Moncada; Jean-Marcel Travere; Thierry Loarer; François Brémond; Guillaume Charpiat; Monique Thonnat (ICVS, 2011)

Learning to Match Appearances by Correlations in a Covariance Metric Space. - Slawomir Bak; Guillaume Charpiat; Etienne Corvée; François Brémond; Monique Thonnat (ECCV (3), 2012)

Enforcing Monotonous Shape Growth or Shrinkage in Video Segmentation. - Yuliya Tarabalka; Guillaume Charpiat; Ludovic Brucker; Bjoern H. Menze (BMVC, 2013)

An efficient optimizer for simple point process models. - Ahmed Gamal-Eldin; Guillaume Charpiat; Xavier Descombes; Josiane Zerubia (Computational Imaging, 2013)

A graph-cut-based method for spatio-temporal segmentation of fire from satellite observations. - Yuliya Tarabalka; Guillaume Charpiat (IGARSS, 2013)

Multiple Object Tracking by Efficient Graph Partitioning. - Ratnesh Kumar 003; Guillaume Charpiat; Monique Thonnat (ACCV (4), 2014)

Hierarchical representation of videos with spatio-temporal fibers. - Ratnesh Kumar 003; Guillaume Charpiat; Monique Thonnat (WACV, 2014)

Spatio-Temporal Video Segmentation With Shape Growth or Shrinkage Constraint. - Yuliya Tarabalka; Guillaume Charpiat; Ludovic Brucker; Bjoern H. Menze (IEEE Trans. Image Process., 2014)

Optimizing Partition Trees for Multi-Object Segmentation with Shape Prior. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat (BMVC, 2015)

Improved partition trees for multi-class segmentation of remote sensing images. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat (IGARSS, 2015)

A Nonparametric Growth Model for Brain Tumor Segmentation in Longitudinal MR Sequences. - Esther Alberts; Guillaume Charpiat; Yuliya Tarabalka; Thomas Huber; Marc-André Weber; Jan S. Bauer; Claus Zimmer; Bjoern H. Menze (Brainles@MICCAI, 2015)

Training recurrent networks online without backtracking. - Yann Ollivier; Guillaume Charpiat (CoRR, 2015)

Fully convolutional neural networks for remote sensing image classification. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (IGARSS, 2016)

Recurrent Neural Networks to Enhance Satellite Image Classification Maps. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (CoRR, 2016)

High-Resolution Semantic Labeling with Convolutional Neural Networks. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (CoRR, 2016)

Polygonization of remote sensing classification maps by mesh approximation. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (ICIP, 2017)

Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (IGARSS, 2017)

High-resolution image classification with convolutional networks. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (IGARSS, 2017)

Online Recognition of Daily Activities by Color-Depth Sensing and Knowledge Models. - Carlos Fernando Crispim Junior; Alvaro Gómez Uría; Carola Strumia; Michal Koperski; Alexandra König; Farhood Negin; Serhan Cosar; Anh-Tuan Nghiem; Duc Phu Chau; Guillaume Charpiat; François Brémond (Sensors, 2017)

Recurrent Neural Networks to Correct Satellite Image Classification Maps. - Emmanuel Maggiori; Guillaume Charpiat; Yuliya Tarabalka; Pierre Alliez (IEEE Trans. Geosci. Remote. Sens., 2017)

Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (IEEE Trans. Geosci. Remote. Sens., 2017)

High-Resolution Aerial Image Labeling With Convolutional Neural Networks. - Emmanuel Maggiori; Yuliya Tarabalka; Guillaume Charpiat; Pierre Alliez (IEEE Trans. Geosci. Remote. Sens., 2017)

Aligning and Updating Cadaster Maps with Aerial Images by Multi-task, Multi-resolution Deep Learning. - Nicolas Girard; Guillaume Charpiat; Yuliya Tarabalka (ACCV (5), 2018)

Multimodal Image Alignment Through a Multiscale Chain of Neural Networks with Application to Remote Sensing. - Armand Zampieri; Guillaume Charpiat; Nicolas Girard; Yuliya Tarabalka (ECCV (16), 2018)

Coarse to fine non-rigid registration: a chain of scale-specific neural networks for multimodal image alignment with application to remote sensing. - Armand Zampieri; Guillaume Charpiat; Yuliya Tarabalka (CoRR, 2018)

Optimizing deep video representation to match brain activity. - Hugo Richard; Ana Luísa Pinho; Bertrand Thirion; Guillaume Charpiat (CoRR, 2018)

Noisy Supervision for Correcting Misaligned Cadaster Maps Without Perfect Ground Truth Data. - Nicolas Girard; Guillaume Charpiat; Yuliya Tarabalka (IGARSS, 2019)

Multi-Task Deep Learning for Satellite Image Pansharpening and Segmentation. - Andrew Khalel; Onur Tasar; Guillaume Charpiat; Yuliya Tarabalka (IGARSS, 2019)

Input Similarity from the Neural Network Perspective. - Guillaume Charpiat; Nicolas Girard; Loris Felardos; Yuliya Tarabalka (NeurIPS, 2019)

CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators. - Julien Girard-Satabin; Guillaume Charpiat; Zakaria Chihani; Marc Schoenauer (ECAI, 2020)

Interpreting a Penalty as the Influence of a Bayesian Prior. - Pierre Wolinski; Guillaume Charpiat; Yann Ollivier (CoRR, 2020)

Tropical Cyclone Track Forecasting Using Fused Deep Learning From Aligned Reanalysis Data. - Sophie Giffard-Roisin; Mo Yang; Guillaume Charpiat; Christina Kumler-Bonfanti; Balázs Kégl; Claire Monteleoni (Frontiers Big Data, 2020)

DISCO Verification: Division of Input Space into COnvex polytopes for neural network verification. - Julien Girard-Satabin; Aymeric Varasse; Marc Schoenauer; Guillaume Charpiat; Zakaria Chihani (CoRR, 2021)

Docent: A content-based recommendation system to discover contemporary art. - Antoine Fosset; Mohamed El-Mennaoui; Amine Rebei; Paul Calligaro; Elise Farge Di Maria; Hélène Nguyen-Ban; Francesca Rea; Marie-Charlotte Vallade; Elisabetta Vitullo; Christophe Zhang; Guillaume Charpiat; Mathieu Rosenbaum (CoRR, 2022)

Machine Learning model for gas-liquid interface reconstruction in CFD numerical simulations. - Tamon Nakano; Alessandro Michele Bucci; Jean-Marc Gratien; Thibault Faney; Guillaume Charpiat (CoRR, 2022)

SE(3)-equivariant Graph Neural Networks for Learning Glassy Liquids Representations. - Francesco Saverio Pezzicoli; Guillaume Charpiat; François P. Landes (CoRR, 2022)

DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations). - Matthieu Nastorg; Marc Schoenauer; Guillaume Charpiat; Thibault Faney; Jean-Marc Gratien; Michele Alessandro Bucci (CoRR, 2022)

Towards creating longer genetic sequences with GANs: Generation in principal component space. - Antoine Szatkownik; Cyril Furtlehner; Guillaume Charpiat; Burak Yelmen; Flora Jay (MLCB, 2023)

Designing losses for data-free training of normalizing flows on Boltzmann distributions. - Loris Felardos; Jérôme Hénin; Guillaume Charpiat (CoRR, 2023)

Neural State-Dependent Delay Differential Equations. - Thibault Monsel; Onofrio Semeraro; Lionel Mathelin; Guillaume Charpiat (CoRR, 2023)

dnadna: a deep learning framework for population genetics inference. - Théophile Sanchez; Erik Madison Bray; Pierre Jobic; Jérémy Guez; Anne-Catherine Letournel; Guillaume Charpiat; Jean Cury; Flora Jay (Bioinform., 2023)

Deep convolutional and conditional neural networks for large-scale genomic data generation. - Burak Yelmen; Aurélien Decelle; Leila Lea Boulos; Antoine Szatkownik; Cyril Furtlehner; Guillaume Charpiat; Flora Jay (PLoS Comput. Biol., 2023)

Multi-Level GNN Preconditioner for Solving Large Scale Problems. - Matthieu Nastorg; Jean-Marc Gratien; Thibault Faney; Michele Alessandro Bucci; Guillaume Charpiat; Marc Schoenauer (IPDPS (Workshops), 2024)

An implicit GNN solver for Poisson-like problems. - Matthieu Nastorg; Michele Alessandro Bucci; Thibault Faney; Jean-Marc Gratien; Guillaume Charpiat; Marc Schoenauer (Comput. Math. Appl., 2024)

Growing Tiny Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally. - Manon Verbockhaven; Sylvain Chevallier; Guillaume Charpiat (CoRR, 2024)

Neural DDEs with Learnable Delays for Partially Observed Dynamical Systems. - Thibault Monsel; Emmanuel Menier; Onofrio Semeraro; Lionel Mathelin; Guillaume Charpiat (CoRR, 2024)

Growing Tiny Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally. - Manon Verbockhaven; Théo Rudkiewicz; Sylvain Chevallier; Guillaume Charpiat (Trans. Mach. Learn. Res., 2024)

Growth strategies for arbitrary DAG neural architectures. - Stella Douka; Manon Verbockhaven; Théo Rudkiewicz; Stéphane Rivaud; François P. Landes; Sylvain Chevallier; Guillaume Charpiat (CoRR, 2025)