Pierre Chainais

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 45

Top Topics

Inference Problems

Bayesian Nonparametric

Top Venues

IEEE Trans. Signal Process.

Publications

Markus Grimm, Sébastien Paul, Pierre Chainais
Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems. Comput. Chem. Eng. 189 (2024)
Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger
Benchmarking multi-component signal processing methods in the time-frequency plane. CoRR (2024)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Plug-and-Play Split Gibbs Sampler: Embedding Deep Generative Priors in Bayesian Inference. IEEE Trans. Image Process. 33 (2024)
Pierre Palud, Pierre-Antoine Thouvenin, Pierre Chainais, Emeric Bron, Franck Le Petit
Efficient Sampling of Non Log-Concave Posterior Distributions With Mixture of Noises. IEEE Trans. Signal Process. 71 (2023)
Sebastian Miron, Julien Flamant, Nicolas Le Bihan, Pierre Chainais, David Brie
Quaternions in Signal and Image Processing: A comprehensive and objective overview. IEEE Signal Process. Mag. 40 (6) (2023)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Normalizing flow sampling with Langevin dynamics in the latent space. CoRR (2023)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Signal reconstruction using determinantal sampling. CoRR (2023)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference. CoRR (2023)
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
Mixture of noises and sampling of non-log-concave posterior distributions. EUSIPCO (2022)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm. SIAM Rev. 64 (1) (2022)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. ESANN (2022)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows. ECML/PKDD (5) (2022)
Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
A versatile distributed MCMC algorithm for large scale inverse problems. EUSIPCO (2022)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Learning Optimal Transport Between two Empirical Distributions with Normalizing Flows. CoRR (2022)
Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
A distributed Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems. CoRR (2022)
Clémence Prévost, Pierre Chainais, Rémy Boyer
Fast Fusion of Hyperspectral and Multispectral Images: A Tucker Approximation Approach. ICIP (2022)
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. CoRR (2022)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms. J. Comput. Graph. Stat. 30 (2) (2021)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel interpolation with continuous volume sampling. ICML (2020)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel interpolation with continuous volume sampling. CoRR (2020)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
A determinantal point process for column subset selection. J. Mach. Learn. Res. 21 (2020)
Maxime Vono, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, Fraçois 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
A Fully Bayesian Approach For Inferring Physical Properties With Credibility Intervals From Noisy Astronomical Data. WHISPERS (2019)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Split-and-Augmented Gibbs Sampler - Application to Large-Scale Inference Problems. IEEE Trans. Signal Process. 67 (6) (2019)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Asymptotically exact data augmentation: models, properties and algorithms. CoRR (2019)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel quadrature with DPPs. NeurIPS (2019)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel quadrature with DPPs. CoRR (2019)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Bayesian Image Restoration under Poisson Noise and Log-concave Prior. ICASSP (2019)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models. ICASSP (2019)
Julien Flamant, Pierre Chainais, Éric Chassande-Mottin, Fangchen Feng, Nicolas Le Bihan
Non-parametric characterization of gravitational-wave polarizations. EUSIPCO (2018)
Julien Flamant, Pierre Chainais, Nicolas Le Bihan
A Complete Framework for Linear Filtering of Bivariate Signals. IEEE Trans. Signal Process. 66 (17) (2018)
Julien Flamant, Pierre Chainais, Nicolas Le Bihan
Linear Filtering of Bivariate Signals Using Quaternions. SSP (2018)
Hong Phuong Dang, Pierre Chainais
Towards Dictionaries of Optimal Size: A Bayesian Non Parametric Approach. J. Signal Process. Syst. 90 (2) (2018)
Maxime Vono, Nicolas Dobigeon, Pierre Chainais
Sparse Bayesian Binary logistic Regression using the Split-and-Augmented Gibbs sampler. MLSP (2018)
Clement Elvira, Hong Phuong Dang, Pierre Chainais
Small variance asymptotics and bayesian nonparametrics for dictionary learning. EUSIPCO (2018)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
A determinantal point process for column subset selection. CoRR (2018)
Hong Phuong Dang, Pierre Chainais
Indian Buffet Process dictionary learning: Algorithms and applications to image processing. Int. J. Approx. Reason. 83 (2017)
Julien Flamant, Nicolas Le Bihan, Pierre Chainais
Spectral Analysis of Stationary Random Bivariate Signals. IEEE Trans. Signal Process. 65 (23) (2017)
Clement Elvira, Pierre Chainais, Nicolas Dobigeon
Bayesian nonparametric subspace estimation. ICASSP (2017)
Julien Flamant, Pierre Chainais, Nicolas Le Bihan
Polarization spectrogram of bivariate signals. ICASSP (2017)
Clement Elvira, Pierre Chainais, Nicolas Dobigeon
Bayesian Antisparse Coding. IEEE Trans. Signal Process. 65 (7) (2017)
Pierre Chainais, Aymeric Leray
Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations. IEEE Trans. Image Process. 25 (4) (2016)
Clement Elvira, Pierre Chainais, Nicolas Dobigeon
Democratic prior for anti-sparse coding. SSP (2016)
Hong Phuong Dang, Pierre Chainais
Indian Buffet process dictionary learning for image inpainting. SSP (2016)
Hong Phuong Dang, Pierre Chainais
A Bayesian non parametric approach to learn dictionaries with adapted numbers of atoms. MLSP (2015)
Sylvain Rousseau, Pierre Chainais, Christelle Garnier
Dictionary learning for a sparse appearance model in visual tracking. ICIP (2015)
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
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). CoRR (2014)
Pierre Chainais, Pierre Pfennig, Aymeric Leray
Quantitative control of the error bounds of a fast super-resolution technique for microscopy and astronomy. ICASSP (2014)
Pierre Chainais, Cédric Richard
Distributed dictionary learning over a sensor network CoRR (2013)
Pierre Chainais, Cédric Richard
Learning a common dictionary over a sensor network. CAMSAP (2013)
Pierre Chainais
Towards dictionary learning from images with non Gaussian noise. MLSP (2012)
Pierre Chainais, Véronique Delouille, Jean-François Hochedez
Scale invariant images in astronomy through the lens of multifractal modeling. ICIP (2011)
Pierre Chainais, Emilie Koenig, Véronique Delouille, Jean-François Hochedez
Virtual Super Resolution of Scale Invariant Textured Images Using Multifractal Stochastic Processes. J. Math. Imaging Vis. 39 (1) (2011)
Patrice Abry, Pierre Chainais, Laure Coutin, Vladas Pipiras
Multifractal random walks as fractional Wiener integrals. IEEE Trans. Inf. Theory 55 (8) (2009)
Emilie Koenig, Pierre Chainais
Virtual resolution enhancement of scale invariant textured images using stochastic processes. ICIP (2009)
Emilie Koenig, Pierre Chainais
Multifractal Analysis on the Sphere. ICISP (2008)
Pierre Chainais
Infinitely Divisible Cascades to Model the Statistics of Natural Images. IEEE Trans. Pattern Anal. Mach. Intell. 29 (12) (2007)
Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system. ESANN (2006)
Alexandre Aussem, Pierre Chainais
Modelling switching dynamics using prediction experts operating on distinct wavelet scales. ESANN (2006)
Pierre Chainais, Rudolf H. Riedi, Patrice Abry
On non-scale-invariant infinitely divisible cascades. IEEE Trans. Inf. Theory 51 (3) (2005)
Pierre Chainais
Multi-dimensional infinitely divisible cascades to model the statistics of natural images. ICIP (3) (2005)
Bruno Lashermes, Patrice Abry, Pierre Chainais
Scaling exponents estimation for multiscaling processes. ICASSP (2) (2004)
Bruno Lashermes, Patrice Abry, Pierre Chainais
New Insights into the Estimation of Scaling Exponents. Int. J. Wavelets Multiresolution Inf. Process. 2 (4) (2004)
Pierre Chainais, Patrice Abry, Darryl Veitch
Multifractal analysis and α-stable processes: a methodological contribution. ICASSP (2000)
Darryl Veitch, Patrice Abry, Patrick Flandrin, Pierre Chainais
Infinitely divisible cascade analysis of network traffic data. ICASSP (2000)