Pierre Chainais
Orcid: 0000-0003-4377-7584
According to our database1,
Pierre Chainais
authored at least 59 papers
between 2000 and 2024.
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Bibliography
2024
Mach. Learn., December, 2024
Plug-and-Play Split Gibbs Sampler: Embedding Deep Generative Priors in Bayesian Inference.
IEEE Trans. Image Process., 2024
CoRR, 2024
Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems.
Comput. Chem. Eng., 2024
Proceedings of the 32nd European Signal Processing Conference, 2024
2023
IEEE Signal Process. Mag., September, 2023
Efficient Sampling of Non Log-Concave Posterior Distributions With Mixture of Noises.
IEEE Trans. Signal Process., 2023
2022
High-Dimensional Gaussian Sampling: A Review and a Unifying Approach Based on a Stochastic Proximal Point Algorithm.
SIAM Rev., 2022
A distributed Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems.
CoRR, 2022
Learning Optimal Transport Between Two Empirical Distributions with Normalizing Flows.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
Fast Fusion of Hyperspectral and Multispectral Images: A Tucker Approximation Approach.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
Proceedings of the 30th European Signal Processing Conference, 2022
Proceedings of the 30th European Signal Processing Conference, 2022
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022
2021
J. Comput. Graph. Stat., 2021
2020
J. Mach. Learn. Res., 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
IEEE Trans. Signal Process., 2019
A Fully Bayesian Approach For Inferring Physical Properties With Credibility Intervals From Noisy Astronomical Data.
Proceedings of the 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
2018
J. Signal Process. Syst., 2018
IEEE Trans. Signal Process., 2018
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018
Sparse Bayesian Binary logistic Regression using the Split-and-Augmented Gibbs sampler.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018
Proceedings of the 26th European Signal Processing Conference, 2018
Proceedings of the 26th European Signal Processing Conference, 2018
2017
IEEE Trans. Signal Process., 2017
Indian Buffet Process dictionary learning: Algorithms and applications to image processing.
Int. J. Approx. Reason., 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
2016
Statistical Performance Analysis of a Fast Super-Resolution Technique Using Noisy Translations.
IEEE Trans. Image Process., 2016
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016
2015
A Bayesian non parametric approach to learn dictionaries with adapted numbers of atoms.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015
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).
CoRR, 2014
Quantitative control of the error bounds of a fast super-resolution technique for microscopy and astronomy.
Proceedings of the IEEE International Conference on Acoustics, 2014
2013
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013
2012
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.
J. Math. Imaging Vis., 2011
Proceedings of the 18th IEEE International Conference on Image Processing, 2011
2009
IEEE Trans. Inf. Theory, 2009
Virtual resolution enhancement of scale invariant textured images using stochastic processes.
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).
, 2009
2008
Proceedings of the Image and Signal Processing - 3rd International Conference, 2008
2007
IEEE Trans. Pattern Anal. Mach. Intell., 2007
2006
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006
Modelling switching dynamics using prediction experts operating on distinct wavelet scales.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006
2005
Multi-dimensional infinitely divisible cascades to model the statistics of natural images.
Proceedings of the 2005 International Conference on Image Processing, 2005
2004
Int. J. Wavelets Multiresolution Inf. Process., 2004
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004
2000
Proceedings of the IEEE International Conference on Acoustics, 2000
Proceedings of the IEEE International Conference on Acoustics, 2000