Pierre Chainais

74 papers A* 2B 7C 1Misc 7Journal 37Unranked 19

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Distributed Plug-and-Play MCMC Algorithm for High-Dimensional Inverse Problems. CoRR Maxime Bouton, Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
2025	—	`conf`	Adaptive hyperparameter tuning for time-frequency algorithms based on the zeros of the spectrogram. SSP Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger
2025	—	`conf`	Multi-GPU distributed PnP-ULA for high-dimensional imaging inverse problems. SSP Maxime Bouton, Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
2025	J	`jnl`	Optimal estimation of the canonical polyadic decomposition from low-rank tensor trains. Signal Process. Clémence Prévost, Pierre Chainais
2025	—	`conf`	Time and covariance smoothing for restoration of bivariate signals. SSP Yusuf Yigit Pilavci, Pierre Palud, Julien Flamant, Pierre-Antoine Thouvenin, Jérémie Boulanger, Pierre Chainais
2024	J	`jnl`	A Distributed Block-Split Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems. J. Comput. Graph. Stat. Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
2024	J	`jnl`	Benchmarking multi-component signal processing methods in the time-frequency plane. CoRR Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger
2024	—	`conf`	Denoising Bivariate Signals via Smoothing and Polarization Priors. EUSIPCO Yusuf Yigit Pilavci, Jérémie Boulanger, Pierre-Antoine Thouvenin, Pierre Chainais
2024	J	`jnl`	Normalizing flow sampling with Langevin dynamics in the latent space. Mach. Learn. Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2024	J	`jnl`	Plug-and-Play Split Gibbs Sampler: Embedding Deep Generative Priors in Bayesian Inference. IEEE Trans. Image Process. Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2024	J	`jnl`	Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems. Comput. Chem. Eng. Markus Grimm, Sébastien Paul, Pierre Chainais
2024	J	`jnl`	Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems. CoRR Markus Grimm, Sébastien Paul, Pierre Chainais
2023	J	`jnl`	Efficient Sampling of Non Log-Concave Posterior Distributions With Mixture of Noises. IEEE Trans. Signal Process. Pierre Palud, Pierre-Antoine Thouvenin, Pierre Chainais, Emeric Bron, Franck Le Petit
2023	J	`jnl`	Normalizing flow sampling with Langevin dynamics in the latent space. CoRR Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2023	J	`jnl`	Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference. CoRR Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2023	J	`jnl`	Quaternions in Signal and Image Processing: A comprehensive and objective overview. IEEE Signal Process. Mag. Sebastian Miron, Julien Flamant, Nicolas Le Bihan, Pierre Chainais, David Brie
2023	J	`jnl`	Signal reconstruction using determinantal sampling. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2022	J	`jnl`	A distributed Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems. CoRR Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
2022	—	`conf`	A versatile distributed MCMC algorithm for large scale inverse problems. EUSIPCO Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais
2022	B	`conf`	Fast Fusion of Hyperspectral and Multispectral Images: A Tucker Approximation Approach. ICIP Clémence Prévost, Pierre Chainais, Rémy Boyer
2022	J	`jnl`	High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm. SIAM Rev. Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2022	—	`conf`	Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows. ECML/PKDD (5) Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2022	J	`jnl`	Learning Optimal Transport Between two Empirical Distributions with Normalizing Flows. CoRR Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2022	—	`conf`	Mixture of noises and sampling of non-log-concave posterior distributions. EUSIPCO 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
2022	B	`conf`	Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. ESANN Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2022	J	`jnl`	Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. CoRR Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
2021	J	`jnl`	Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms. J. Comput. Graph. Stat. Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2020	J	`jnl`	A determinantal point process for column subset selection. J. Mach. Learn. Res. Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2020	A*	`conf`	Kernel interpolation with continuous volume sampling. ICML Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2020	J	`jnl`	Kernel interpolation with continuous volume sampling. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2019	—	`conf`	A Fully Bayesian Approach For Inferring Physical Properties With Credibility Intervals From Noisy Astronomical Data. WHISPERS 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
2019	J	`jnl`	Asymptotically exact data augmentation: models, properties and algorithms. CoRR Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2019	Misc	`conf`	Bayesian Image Restoration under Poisson Noise and Log-concave Prior. ICASSP Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2019	Misc	`conf`	Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models. ICASSP Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2019	A*	`conf`	Kernel quadrature with DPPs. NeurIPS Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2019	J	`jnl`	Kernel quadrature with DPPs. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2019	J	`jnl`	Split-and-Augmented Gibbs Sampler - Application to Large-Scale Inference Problems. IEEE Trans. Signal Process. Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2018	J	`jnl`	A Complete Framework for Linear Filtering of Bivariate Signals. IEEE Trans. Signal Process. Julien Flamant, Pierre Chainais, Nicolas Le Bihan
2018	J	`jnl`	A determinantal point process for column subset selection. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2018	—	`conf`	Linear Filtering of Bivariate Signals Using Quaternions. SSP Julien Flamant, Pierre Chainais, Nicolas Le Bihan
2018	—	`conf`	Non-parametric characterization of gravitational-wave polarizations. EUSIPCO Julien Flamant, Pierre Chainais, Éric Chassande-Mottin, Fangchen Feng, Nicolas Le Bihan
2018	—	`conf`	Small variance asymptotics and bayesian nonparametrics for dictionary learning. EUSIPCO Clement Elvira, Hong Phuong Dang, Pierre Chainais
2018	—	`conf`	Sparse Bayesian Binary logistic Regression using the Split-and-Augmented Gibbs sampler. MLSP Maxime Vono, Nicolas Dobigeon, Pierre Chainais
2018	J	`jnl`	Towards Dictionaries of Optimal Size: A Bayesian Non Parametric Approach. J. Signal Process. Syst. Hong Phuong Dang, Pierre Chainais
2017	J	`jnl`	Bayesian Antisparse Coding. IEEE Trans. Signal Process. Clement Elvira, Pierre Chainais, Nicolas Dobigeon
2017	Misc	`conf`	Bayesian nonparametric subspace estimation. ICASSP Clement Elvira, Pierre Chainais, Nicolas Dobigeon
2017	J	`jnl`	Indian Buffet Process dictionary learning: Algorithms and applications to image processing. Int. J. Approx. Reason. Hong Phuong Dang, Pierre Chainais
2017	Misc	`conf`	Polarization spectrogram of bivariate signals. ICASSP Julien Flamant, Pierre Chainais, Nicolas Le Bihan
2017	J	`jnl`	Spectral Analysis of Stationary Random Bivariate Signals. IEEE Trans. Signal Process. Julien Flamant, Nicolas Le Bihan, Pierre Chainais
2016	—	`conf`	Democratic prior for anti-sparse coding. SSP Clement Elvira, Pierre Chainais, Nicolas Dobigeon
2016	—	`conf`	Indian Buffet process dictionary learning for image inpainting. SSP Hong Phuong Dang, Pierre Chainais
2016	J	`jnl`	Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations. IEEE Trans. Image Process. Pierre Chainais, Aymeric Leray
2015	—	`conf`	A Bayesian non parametric approach to learn dictionaries with adapted numbers of atoms. MLSP Hong Phuong Dang, Pierre Chainais
2015	B	`conf`	Dictionary learning for a sparse appearance model in visual tracking. ICIP Sylvain Rousseau, Pierre Chainais, Christelle Garnier
2014	J	`jnl`	Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). CoRR 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
2014	Misc	`conf`	Quantitative control of the error bounds of a fast super-resolution technique for microscopy and astronomy. ICASSP Pierre Chainais, Pierre Pfennig, Aymeric Leray
2013	J	`jnl`	Distributed dictionary learning over a sensor network CoRR Pierre Chainais, Cédric Richard
2013	—	`conf`	Learning a common dictionary over a sensor network. CAMSAP Pierre Chainais, Cédric Richard
2012	—	`conf`	Towards dictionary learning from images with non Gaussian noise. MLSP Pierre Chainais
2011	B	`conf`	Scale invariant images in astronomy through the lens of multifractal modeling. ICIP Pierre Chainais, Véronique Delouille, Jean-François Hochedez
2011	J	`jnl`	Virtual Super Resolution of Scale Invariant Textured Images Using Multifractal Stochastic Processes. J. Math. Imaging Vis. Pierre Chainais, Emilie Koenig, Véronique Delouille, Jean-François Hochedez
2009	J	`jnl`	Multifractal random walks as fractional Wiener integrals. IEEE Trans. Inf. Theory Patrice Abry, Pierre Chainais, Laure Coutin, Vladas Pipiras
2009	—	`book`	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	B	`conf`	Virtual resolution enhancement of scale invariant textured images using stochastic processes. ICIP Emilie Koenig, Pierre Chainais
2008	C	`conf`	Multifractal Analysis on the Sphere. ICISP Emilie Koenig, Pierre Chainais
2007	J	`jnl`	Infinitely Divisible Cascades to Model the Statistics of Natural Images. IEEE Trans. Pattern Anal. Mach. Intell. Pierre Chainais
2006	B	`conf`	Modelling switching dynamics using prediction experts operating on distinct wavelet scales. ESANN Alexandre Aussem, Pierre Chainais
2006	B	`conf`	Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system. ESANN Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem
2005	—	`conf`	Multi-dimensional infinitely divisible cascades to model the statistics of natural images. ICIP (3) Pierre Chainais
2005	J	`jnl`	On non-scale-invariant infinitely divisible cascades. IEEE Trans. Inf. Theory Pierre Chainais, Rudolf H. Riedi, Patrice Abry
2004	J	`jnl`	New Insights into the Estimation of Scaling Exponents. Int. J. Wavelets Multiresolution Inf. Process. Bruno Lashermes, Patrice Abry, Pierre Chainais
2004	—	`conf`	Scaling exponents estimation for multiscaling processes. ICASSP (2) Bruno Lashermes, Patrice Abry, Pierre Chainais
2000	Misc	`conf`	Infinitely divisible cascade analysis of network traffic data. ICASSP Darryl Veitch, Patrice Abry, Patrick Flandrin, Pierre Chainais
2000	Misc	`conf`	Multifractal analysis and α-stable processes: a methodological contribution. ICASSP Pierre Chainais, Patrice Abry, Darryl Veitch