Pierre Chainais

According to our database, Pierre Chainais authored at least 57 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Benchmarking multi-component signal processing methods in the time-frequency plane.

Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger

CoRR, 2024

2023

Quaternions in Signal and Image Processing: A comprehensive and objective overview.

Sebastian Miron, Julien Flamant, Nicolas Le Bihan, Pierre Chainais, David Brie

IEEE Signal Process. Mag., September, 2023

Efficient Sampling of Non Log-Concave Posterior Distributions With Mixture of Noises.

Pierre Palud, Pierre-Antoine Thouvenin, Pierre Chainais, Emeric Bron, Franck Le Petit

IEEE Trans. Signal Process., 2023

Signal reconstruction using determinantal sampling.

Ayoub Belhadji, Rémi Bardenet, Pierre Chainais

CoRR, 2023

Normalizing flow sampling with Langevin dynamics in the latent space.

Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais

CoRR, 2023

Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference.

Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais

CoRR, 2023

2022

High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm.

Maxime Vono, Nicolas Dobigeon, Pierre Chainais

SIAM Rev., 2022

A distributed Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems.

Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais

CoRR, 2022

Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows.

Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Fast Fusion of Hyperspectral and Multispectral Images: A Tucker Approximation Approach.

Clémence Prévost, Pierre Chainais, Rémy Boyer

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

A versatile distributed MCMC algorithm for large scale inverse problems.

Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais

Proceedings of the 30th European Signal Processing Conference, 2022

Mixture of noises and sampling of non-log-concave posterior distributions.

Pierre Palud, Pierre Chainais, Franck Le Petit, Emeric Bron, Pierre-Antoine Thouvenin, Maxime Vono, L. Einig, M. Garcia Santa-Maria, Mathilde Gaudel, Jan H. Orkisz, Victor de Souza Magalhaes, Sébastien Bardeau, Maryvonne Gerin, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Jouni Kainulainen, François Levrier, Nicolas Peretto, Jérome Pety, Antoine Roueff, Albrecht Sievers

Proceedings of the 30th European Signal Processing Conference, 2022

Sliced-Wasserstein normalizing flows: beyond maximum likelihood training.

Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms.

Maxime Vono, Nicolas Dobigeon, Pierre Chainais

J. Comput. Graph. Stat., 2021

2020

A determinantal point process for column subset selection.

Ayoub Belhadji, Rémi Bardenet, Pierre Chainais

J. Mach. Learn. Res., 2020

Kernel interpolation with continuous volume sampling.

Ayoub Belhadji, Rémi Bardenet, Pierre Chainais

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Split-and-Augmented Gibbs Sampler - Application to Large-Scale Inference Problems.

Maxime Vono, Nicolas Dobigeon, Pierre Chainais

IEEE Trans. Signal Process., 2019

A Fully Bayesian Approach For Inferring Physical Properties With Credibility Intervals From Noisy Astronomical Data.

Maxime Vono, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, François Levrier, Harvey S. Listz, Karin I. Oberg, Emeric Bron, Jan H. Orkisz, Nicolas Peretto, Jérome Pety, Antoine Roueff, Èvelyne Roueff, Albrecht Sievers, Victor de Souza Magalhaes, Pascal Tremblin, Pierre Chainais, Franck Le Petit, Sébastien Bardeau, Sébastien Bourguignon, Jocelyn Chanussot, Mathilde Gaudel, Maryvonne Gerin

Proceedings of the 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2019

Kernel quadrature with DPPs.

Ayoub Belhadji, Rémi Bardenet, Pierre Chainais

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models.

Maxime Vono, Nicolas Dobigeon, Pierre Chainais

Proceedings of the IEEE International Conference on Acoustics, 2019

Bayesian Image Restoration under Poisson Noise and Log-concave Prior.

Maxime Vono, Nicolas Dobigeon, Pierre Chainais

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Towards Dictionaries of Optimal Size: A Bayesian Non Parametric Approach.

Hong Phuong Dang, Pierre Chainais

J. Signal Process. Syst., 2018

A Complete Framework for Linear Filtering of Bivariate Signals.

Julien Flamant, Pierre Chainais, Nicolas Le Bihan

IEEE Trans. Signal Process., 2018

Linear Filtering of Bivariate Signals Using Quaternions.

Julien Flamant, Pierre Chainais, Nicolas Le Bihan

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Sparse Bayesian Binary logistic Regression using the Split-and-Augmented Gibbs sampler.

Maxime Vono, Nicolas Dobigeon, Pierre Chainais

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Non-parametric characterization of gravitational-wave polarizations.

Julien Flamant, Pierre Chainais, Éric Chassande-Mottin, Fangchen Feng, Nicolas Le Bihan

Proceedings of the 26th European Signal Processing Conference, 2018

Small variance asymptotics and bayesian nonparametrics for dictionary learning.

Clement Elvira, Hong Phuong Dang, Pierre Chainais

Proceedings of the 26th European Signal Processing Conference, 2018

2017

Spectral Analysis of Stationary Random Bivariate Signals.

Julien Flamant, Nicolas Le Bihan, Pierre Chainais

IEEE Trans. Signal Process., 2017

Bayesian Antisparse Coding.

Clement Elvira, Pierre Chainais, Nicolas Dobigeon

IEEE Trans. Signal Process., 2017

Indian Buffet Process dictionary learning: Algorithms and applications to image processing.

Hong Phuong Dang, Pierre Chainais

Int. J. Approx. Reason., 2017

Polarization spectrogram of bivariate signals.

Julien Flamant, Pierre Chainais, Nicolas Le Bihan

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Bayesian nonparametric subspace estimation.

Clement Elvira, Pierre Chainais, Nicolas Dobigeon

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations.

Pierre Chainais, Aymeric Leray

IEEE Trans. Image Process., 2016

Democratic prior for anti-sparse coding.

Clement Elvira, Pierre Chainais, Nicolas Dobigeon

Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Indian Buffet process dictionary learning for image inpainting.

Hong Phuong Dang, Pierre Chainais

Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

2015

A Bayesian non parametric approach to learn dictionaries with adapted numbers of atoms.

Hong Phuong Dang, Pierre Chainais

Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Dictionary learning for a sparse appearance model in visual tracking.

Sylvain Rousseau, Pierre Chainais, Christelle Garnier

Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

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, Rémi Gribonval, Nicolas Boumal, Bamdev Mishra, Pierre-Antoine Absil, Rodolphe Sepulchre, Shaun Bundervoet, Colas Schretter, Ann Dooms, Peter Schelkens, Olivier Chabiron, François Malgouyres, Jean-Yves Tourneret, Nicolas Dobigeon, Pierre Chainais, Cédric Richard, Bruno Cornelis, Ingrid Daubechies, David B. Dunson, Marie Danková, Pavel Rajmic, Kévin Degraux, Valerio Cambareri, Bert Geelen, Gauthier Lafruit, Gianluca Setti, Jean-François Determe, Jérôme Louveaux, François Horlin, Angélique Drémeau, Patrick Héas, Cédric Herzet, Vincent Duval, Gabriel Peyré, Alhussein Fawzi, Mike E. Davies, Nicolas Gillis, Stephen A. Vavasis, Charles Soussen, Luc Le Magoarou, Jingwei Liang, Jalal Fadili, Antoine Liutkus, David Martina, Sylvain Gigan, Laurent Daudet, Mauro Maggioni, Stanislav Minsker, Nate Strawn, C. Mory, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Ignace Loris, Samuel Vaiter, Mohammad Golbabaee, Dejan Vukobratovic

CoRR, 2014

Quantitative control of the error bounds of a fast super-resolution technique for microscopy and astronomy.

Pierre Chainais, Pierre Pfennig, Aymeric Leray

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Distributed dictionary learning over a sensor network

Pierre Chainais, Cédric Richard

CoRR, 2013

Learning a common dictionary over a sensor network.

Pierre Chainais, Cédric Richard

Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012

Towards dictionary learning from images with non Gaussian noise.

Pierre Chainais

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

2011

Virtual Super Resolution of Scale Invariant Textured Images Using Multifractal Stochastic Processes.

Pierre Chainais, Emilie Koenig, Véronique Delouille, Jean-François Hochedez

J. Math. Imaging Vis., 2011

Scale invariant images in astronomy through the lens of multifractal modeling.

Pierre Chainais, Véronique Delouille, Jean-François Hochedez

Proceedings of the 18th IEEE International Conference on Image Processing, 2011

2009

Multifractal random walks as fractional Wiener integrals.

Patrice Abry, Pierre Chainais, Laure Coutin, Vladas Pipiras

IEEE Trans. Inf. Theory, 2009

Virtual resolution enhancement of scale invariant textured images using stochastic processes.

Emilie Koenig, Pierre Chainais

Proceedings of the International Conference on Image Processing, 2009

Processus aléatoires invariants d'échelle et analyse multirésolution pour la modélisation d'observations de systèmes physiques. (Scale invariant stochastic processes and multiresolution analysis for the modeling of physical systems).

Pierre Chainais

, 2009

2008

Multifractal Analysis on the Sphere.

Emilie Koenig, Pierre Chainais

Proceedings of the Image and Signal Processing - 3rd International Conference, 2008

2007

Infinitely Divisible Cascades to Model the Statistics of Natural Images.

Pierre Chainais

IEEE Trans. Pattern Anal. Mach. Intell., 2007

2006

Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system.

Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

Modelling switching dynamics using prediction experts operating on distinct wavelet scales.

Alexandre Aussem, Pierre Chainais

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

2005

On non-scale-invariant infinitely divisible cascades.

Pierre Chainais, Rudolf H. Riedi, Patrice Abry

IEEE Trans. Inf. Theory, 2005

Multi-dimensional infinitely divisible cascades to model the statistics of natural images.

Pierre Chainais

Proceedings of the 2005 International Conference on Image Processing, 2005

2004

New Insights into the Estimation of Scaling Exponents.

Bruno Lashermes, Patrice Abry, Pierre Chainais

Int. J. Wavelets Multiresolution Inf. Process., 2004

Scaling exponents estimation for multiscaling processes.

Bruno Lashermes, Patrice Abry, Pierre Chainais

Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2000

Infinitely divisible cascade analysis of network traffic data.

Darryl Veitch, Patrice Abry, Patrick Flandrin, Pierre Chainais

Proceedings of the IEEE International Conference on Acoustics, 2000

Multifractal analysis and α-stable processes: a methodological contribution.

Pierre Chainais, Patrice Abry, Darryl Veitch

Proceedings of the IEEE International Conference on Acoustics, 2000