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Pierre Chainais
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2020 – today
- 2024
- [j19]Markus Grimm
, Sébastien Paul
Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems. Comput. Chem. Eng. 189: 108779 (2024) - [j18]Florentin Coeurdoux
Plug-and-Play Split Gibbs Sampler: Embedding Deep Generative Priors in Bayesian Inference. IEEE Trans. Image Process. 33: 3496-3507 (2024) - [c33]Yusuf Yigit Pilavci, Jérémie Boulanger, Pierre-Antoine Thouvenin, Pierre Chainais:
Denoising Bivariate Signals via Smoothing and Polarization Priors. EUSIPCO 2024: 2602-2606 - [i14]Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger:
Benchmarking multi-component signal processing methods in the time-frequency plane. CoRR abs/2402.08521 (2024) - [i13]Markus Grimm, Sébastien Paul, Pierre Chainais:
Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems. CoRR abs/2408.02551 (2024) - 2023
- [j17]Sebastian Miron
Quaternions in Signal and Image Processing: A comprehensive and objective overview. IEEE Signal Process. Mag. 40(6): 26-40 (2023) - [j16]Pierre Palud
Efficient Sampling of Non Log-Concave Posterior Distributions With Mixture of Noises. IEEE Trans. Signal Process. 71: 2491-2501 (2023) - [i12]Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference. CoRR abs/2304.11134 (2023) - [i11]Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Normalizing flow sampling with Langevin dynamics in the latent space. CoRR abs/2305.12149 (2023) - [i10]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
Signal reconstruction using determinantal sampling. CoRR abs/2310.09437 (2023) - 2022
- [j15]Maxime Vono
High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm. SIAM Rev. 64(1): 3-56 (2022) - [c32]Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. ESANN 2022 - [c31]Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais:
A versatile distributed MCMC algorithm for large scale inverse problems. EUSIPCO 2022: 2016-2020 - [c30]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: 2031-2035 - [c29]Clémence Prévost, Pierre Chainais, Rémy Boyer:
Fast Fusion of Hyperspectral and Multispectral Images: A Tucker Approximation Approach. ICIP 2022: 2076-2080 - [c28]Florentin Coeurdoux
Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows. ECML/PKDD (5) 2022: 275-290 - [i9]Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Learning Optimal Transport Between two Empirical Distributions with Normalizing Flows. CoRR abs/2207.01246 (2022) - [i8]Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. CoRR abs/2207.05468 (2022) - [i7]Pierre-Antoine Thouvenin, Audrey Repetti, Pierre Chainais:
A distributed Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems. CoRR abs/2210.02341 (2022) - 2021
- [j14]Maxime Vono
Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms. J. Comput. Graph. Stat. 30(2): 335-348 (2021) - 2020
- [j13]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
A determinantal point process for column subset selection. J. Mach. Learn. Res. 21: 197:1-197:62 (2020) - [c27]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
Kernel interpolation with continuous volume sampling. ICML 2020: 725-735 - [i6]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
Kernel interpolation with continuous volume sampling. CoRR abs/2002.09677 (2020)
2010 – 2019
- 2019
- [j12]Maxime Vono
Split-and-Augmented Gibbs Sampler - Application to Large-Scale Inference Problems. IEEE Trans. Signal Process. 67(6): 1648-1661 (2019) - [c26]Maxime Vono
Bayesian Image Restoration under Poisson Noise and Log-concave Prior. ICASSP 2019: 1712-1716 - [c25]Maxime Vono
Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical Models. ICASSP 2019: 5037-5041 - [c24]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
Kernel quadrature with DPPs. NeurIPS 2019: 12907-12917 - [c23]Maxime Vono
A Fully Bayesian Approach For Inferring Physical Properties With Credibility Intervals From Noisy Astronomical Data. WHISPERS 2019: 1-5 - [i5]Maxime Vono, Nicolas Dobigeon, Pierre Chainais:
Asymptotically exact data augmentation: models, properties and algorithms. CoRR abs/1902.05754 (2019) - [i4]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
Kernel quadrature with DPPs. CoRR abs/1906.07832 (2019) - 2018
- [j11]Julien Flamant
A Complete Framework for Linear Filtering of Bivariate Signals. IEEE Trans. Signal Process. 66(17): 4541-4552 (2018) - [j10]Hong Phuong Dang
Towards Dictionaries of Optimal Size: A Bayesian Non Parametric Approach. J. Signal Process. Syst. 90(2): 221-232 (2018) - [c22]Clement Elvira
Small variance asymptotics and bayesian nonparametrics for dictionary learning. EUSIPCO 2018: 1607-1611 - [c21]Julien Flamant, Pierre Chainais, Éric Chassande-Mottin, Fangchen Feng, Nicolas Le Bihan:
Non-parametric characterization of gravitational-wave polarizations. EUSIPCO 2018: 2658-2662 - [c20]Maxime Vono
Sparse Bayesian Binary logistic Regression using the Split-and-Augmented Gibbs sampler. MLSP 2018: 1-6 - [c19]Julien Flamant
Linear Filtering of Bivariate Signals Using Quaternions. SSP 2018: 154-158 - [i3]Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
A determinantal point process for column subset selection. CoRR abs/1812.09771 (2018) - 2017
- [j9]Hong Phuong Dang
Indian Buffet Process dictionary learning: Algorithms and applications to image processing. Int. J. Approx. Reason. 83: 1-20 (2017) - [j8]Clement Elvira
Bayesian Antisparse Coding. IEEE Trans. Signal Process. 65(7): 1660-1672 (2017) - [j7]Julien Flamant
Spectral Analysis of Stationary Random Bivariate Signals. IEEE Trans. Signal Process. 65(23): 6135-6145 (2017) - [c18]Clement Elvira, Pierre Chainais, Nicolas Dobigeon:
Bayesian nonparametric subspace estimation. ICASSP 2017: 2247-2251 - [c17]Julien Flamant
Polarization spectrogram of bivariate signals. ICASSP 2017: 3989-3993 - 2016
- [j6]Pierre Chainais
Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations. IEEE Trans. Image Process. 25(4): 1699-1712 (2016) - [c16]Hong Phuong Dang, Pierre Chainais:
Indian Buffet process dictionary learning for image inpainting. SSP 2016: 1-5 - [c15]Clement Elvira
Democratic prior for anti-sparse coding. SSP 2016: 1-4 - 2015
- [c14]Sylvain Rousseau, Pierre Chainais
Dictionary learning for a sparse appearance model in visual tracking. ICIP 2015: 4506-4510 - [c13]Hong Phuong Dang
A Bayesian non parametric approach to learn dictionaries with adapted numbers of atoms. MLSP 2015: 1-6 - 2014
- [c12]Pierre Chainais
Quantitative control of the error bounds of a fast super-resolution technique for microscopy and astronomy. ICASSP 2014: 2853-2857 - [i2]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 abs/1410.0719 (2014) - 2013
- [c11]Pierre Chainais
Learning a common dictionary over a sensor network. CAMSAP 2013: 133-136 - [i1]Pierre Chainais, Cédric Richard:
Distributed dictionary learning over a sensor network. CoRR abs/1304.3568 (2013) - 2012
- [c10]Pierre Chainais
Towards dictionary learning from images with non Gaussian noise. MLSP 2012: 1-6 - 2011
- [j5]Pierre Chainais
Virtual Super Resolution of Scale Invariant Textured Images Using Multifractal Stochastic Processes. J. Math. Imaging Vis. 39(1): 28-44 (2011) - [c9]Pierre Chainais
Scale invariant images in astronomy through the lens of multifractal modeling. ICIP 2011: 1309-1312
2000 – 2009
- 2009
- [b1]Pierre Chainais:
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). Blaise Pascal University, Clermont-Ferrand, France, 2009 - [j4]Patrice Abry
Multifractal random walks as fractional Wiener integrals. IEEE Trans. Inf. Theory 55(8): 3825-3846 (2009) - [c8]Emilie Koenig, Pierre Chainais
Virtual resolution enhancement of scale invariant textured images using stochastic processes. ICIP 2009: 3137-3140 - 2008
- [c7]Emilie Koenig, Pierre Chainais
Multifractal Analysis on the Sphere. ICISP 2008: 613-621 - 2007
- [j3]Pierre Chainais
Infinitely Divisible Cascades to Model the Statistics of Natural Images. IEEE Trans. Pattern Anal. Mach. Intell. 29(12): 2105-2119 (2007) - 2006
- [c6]Alexandre Aussem, Pierre Chainais:
Modelling switching dynamics using prediction experts operating on distinct wavelet scales. ESANN 2006: 185-190 - [c5]Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem:
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system. ESANN 2006: 659-664 - 2005
- [j2]Pierre Chainais
On non-scale-invariant infinitely divisible cascades. IEEE Trans. Inf. Theory 51(3): 1063-1083 (2005) - [c4]Pierre Chainais
Multi-dimensional infinitely divisible cascades to model the statistics of natural images. ICIP (3) 2005: 129-132 - 2004
- [j1]Bruno Lashermes, Patrice Abry, Pierre Chainais
New Insights into the Estimation of Scaling Exponents. Int. J. Wavelets Multiresolution Inf. Process. 2(4): 497-523 (2004) - [c3]Bruno Lashermes, Patrice Abry, Pierre Chainais
Scaling exponents estimation for multiscaling processes. ICASSP (2) 2004: 509-512 - 2000
- [c2]Pierre Chainais
Multifractal analysis and α-stable processes: a methodological contribution. ICASSP 2000: 241-244 - [c1]Darryl Veitch, Patrice Abry, Patrick Flandrin, Pierre Chainais
Infinitely divisible cascade analysis of network traffic data. ICASSP 2000: 245-248
Coauthor Index
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last updated on 2024-11-07 21:31 CET by the dblp team
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