Scale Space Exploration For Mining Image Information Content. - Mariana Ciucu; Patrick Héas; Mihai Datcu; James C. Tilton (MDM/KDD, 2002)

Image time series mining for dynamic scene understanding. - Patrick Héas; Mihai Datcu; Malika Abdellani; Alain Giros; Philippe Marthon (IGARSS, 2003)

Image time-series mining. - Patrick Héas; Philippe Marthon; Mihai Datcu; Alain Giros (IGARSS, 2004)

Modeling trajectory of dynamic clusters in image time-series for spatio-temporal reasoning. - Patrick Héas; Mihai Datcu (IEEE Trans. Geosci. Remote. Sens., 2005)

Dense Estimation of Layer Motions in the Atmosphere. - Patrick Héas; Étienne Mémin; Nicolas Papadakis (ICPR (3), 2006)

Image Assimilation for Motion Estimation of Atmospheric Layers with Shallow-Water Model. - Nicolas Papadakis; Patrick Héas; Étienne Mémin (ACCV (1), 2007)

A Consistent Spatio-temporal Motion Estimator for Atmospheric Layers. - Patrick Héas; Étienne Mémin; Nicolas Papadakis (SSVM, 2007)

Supervised learning on graphs of spatio-temporal similarity in satellite image sequences - Patrick Héas; Mihai Datcu (CoRR, 2007)

Layered Estimation of Atmospheric Mesoscale Dynamics From Satellite Imagery. - Patrick Héas; Étienne Mémin; Nicolas Papadakis; André Szantai (IEEE Trans. Geosci. Remote. Sens., 2007)

Variational Pressure Image Assimilation for Atmospheric Motion Estimation. - Thomas Corpetti; Patrick Héas; Étienne Mémin; Nicolas Papadakis (IGARSS (2), 2008)

Optical-Flow for 3D Atmospheric Motion Estimation. - Patrick Héas; Étienne Mémin (VISAPP (2), 2008)

Three-Dimensional Motion Estimation of Atmospheric Layers From Image Sequences. - Patrick Héas; Étienne Mémin (IEEE Trans. Geosci. Remote. Sens., 2008)

Bayesian selection of scaling laws for motion modeling in images. - Patrick Héas; Étienne Mémin; Dominique Heitz; Pablo D. Mininni (ICCV, 2009)

Inference on Gibbs Optic-flow Priors : Application to Atmospheric Turbulence Characterization. - Patrick Héas; Étienne Mémin (IGARSS (3), 2009)

Wavelet-Based Fluid Motion Estimation. - Pierre Dérian; Patrick Héas; Cédric Herzet; Étienne Mémin (SSVM, 2011)

Robust Optic-Flow Estimation with Bayesian Inference of Model and Hyper-parameters. - Patrick Héas; Cédric Herzet; Étienne Mémin (SSVM, 2011)

Bayesian Inference of Models and Hyperparameters for Robust Optical-Flow Estimation. - Patrick Héas; Cédric Herzet; Étienne Mémin (IEEE Trans. Image Process., 2012)

Divergence-Free Wavelets and High Order Regularization. - Souleymane Kadri Harouna; Pierre Dérian; Patrick Héas; Étienne Mémin (Int. J. Comput. Vis., 2013)

Bayesian Estimation of Turbulent Motion. - Patrick Héas; Cédric Herzet; Étienne Mémin; Dominique Heitz; Pablo D. Mininni (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Sparse representations in nested non-linear models. - Angélique Dremeau; Patrick Héas; Cédric Herzet (ICASSP, 2014)

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). - Laurent Jacques; Christophe De Vleeschouwer; Yannick Boursier; Prasad Sudhakar; C. De Mol; Aleksandra Pizurica; Sandrine Anthoine; Pierre Vandergheynst; Pascal Frossard; Cagdas Bilen; Srdan Kitic; Nancy Bertin; et al. (CoRR, 2014)

Self-Similar Prior and Wavelet Bases for Hidden Incompressible Turbulent Motion. - Patrick Héas; Frédéric Lavancier; Souleymane Kadri Harouna (SIAM J. Imaging Sci., 2014)

Estimation of Super-Resolved Video Dynamics. - Patrick Héas; Angélique Drémeau; Cédric Herzet (CoRR, 2015)

Reduced-order modeling of hidden dynamics. - Patrick Héas; Cédric Herzet (ICASSP, 2016)

Low-rank Approximation and Dynamic Mode Decomposition. - Patrick Héas; Cédric Herzet (CoRR, 2016)

An Efficient Algorithm for Video Superresolution Based on a Sequential Model. - Patrick Héas; Angélique Drémeau; Cédric Herzet (SIAM J. Imaging Sci., 2016)

Optimal low-rank Dynamic Mode Decomposition. - Patrick Héas; Cédric Herzet (ICASSP, 2017)

Low-rank Approximation of Linear Maps. - Patrick Héas; Cédric Herzet (CoRR, 2018)

Generalized Kernel-Based Dynamic Mode Decomposition. - Patrick Héas; Cédric Herzet; Benoît Combès (ICASSP, 2020)

Selecting Reduced Models in the Cross-Entropy Method. - Patrick Héas (SIAM/ASA J. Uncertain. Quantification, 2020)

State-Of-The-Art Algorithms For Low-Rank Dynamic Mode Decomposition. - Patrick Héas; Cédric Herzet (CoRR, 2021)

Uncertainty of Atmospheric Motion Vectors by Sampling Tempered Posterior Distributions. - Patrick Héas; Frédéric Cérou; Mathias Rousset (CoRR, 2022)

Entropy minimizing distributions are worst-case optimal importance proposals. - Frédéric Cérou; Patrick Héas; Mathias Rousset (CoRR, 2022)

Low-Rank Dynamic Mode Decomposition: An Exact and Tractable Solution. - Patrick Héas; Cédric Herzet (J. Nonlinear Sci., 2022)

3D wind field profiles from hyperspectral sounders: revisiting optic-flow from a meteorological perspective. - Patrick Héas; Olivier Hautecoeur; Régis Borde (CoRR, 2023)

Nonlinear Reduced Modeling of Dynamical Systems Using Kernel Methods and Low-Rank Approximation. - Patrick Héas; Cédric Herzet; Benoît Combès (J. Nonlinear Sci., 2025)