Usages et conception des TIC : Proposition d'un modèle d'aide à la représentation de problème de conception - Pierre Humbert (CoRR, 2010)

Subsampling of Multivariate Time-Vertex Graph Signals. - Pierre Humbert; Laurent Oudre; Nicolas Vayatis (EUSIPCO, 2019)

Learning Laplacian Matrix from Bandlimited Graph Signals. - Batiste Le Bars; Pierre Humbert; Laurent Oudre; Argyris Kalogeratos (ICASSP, 2019)

Multivariate Convolutional Sparse Coding with Low Rank Tensor. - Pierre Humbert; Julien Audiffren; Laurent Oudre; Nicolas Vayatis (CoRR, 2019)

Detecting multiple change-points in the time-varying Ising model. - Batiste Le Bars; Pierre Humbert; Argyris Kalogeratos; Nicolas Vayatis (CoRR, 2019)

Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia. - Clément Dubost; Pierre Humbert; Arno Benizri; Jean-Pierre Tourtier; Nicolas Vayatis; Pierre-Paul Vidal (Frontiers Comput. Neurosci., 2019)

Low Rank Activations for Tensor-Based Convolutional Sparse Coding. - Pierre Humbert; Julien Audiffren; Laurent Oudre; Nicolas Vayatis (ICASSP, 2020)

Learning the piece-wise constant graph structure of a varying Ising model. - Batiste Le Bars; Pierre Humbert; Argyris Kalogeratos; Nicolas Vayatis (ICML, 2020)

Tensor Convolutional Sparse Coding with Low-Rank activations, an application to EEG analysis. - Pierre Humbert; Laurent Oudre; Nicolas Vayatis; Julien Audiffren (CoRR, 2020)

Apprenticeship Learning for a Predictive State Representation of Anesthesia. - Pierre Humbert; Clément Dubost; Julien Audiffren; Laurent Oudre (IEEE Trans. Biomed. Eng., 2020)

Learning spatial filters from EEG signals with Graph Signal Processing methods. - Pierre Humbert; Laurent Oudre; Clément Dubost (EMBC, 2021)

Adaptive Subsampling of Multidomain Signals with Product Graphs. - Théo Gnassounou; Pierre Humbert; Laurent Oudre (ICASSP, 2021)

Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation. - Pierre Humbert; Batiste Le Bars; Laurent Oudre; Argyris Kalogeratos; Nicolas Vayatis (J. Mach. Learn. Res., 2021)

Multivariate analysis with tensors and graphs - application to neuroscience. (Tenseurs et graphes pour l'analyse multivariée - application aux neurosciences). - Pierre Humbert (2021)

Robust Kernel Density Estimation with Median-of-Means principle. - Pierre Humbert; Batiste Le Bars; Ludovic Minvielle (ICML, 2022)

Tensor Convolutional Dictionary Learning With CP Low-Rank Activations. - Pierre Humbert; Laurent Oudre; Nicolas Vayatis; Julien Audiffren (IEEE Trans. Signal Process., 2022)

One-Shot Federated Conformal Prediction. - Pierre Humbert; Batiste Le Bars; Aurélien Bellet; Sylvain Arlot (ICML, 2023)

Using Graph Prior to Learn Network Granger Causality. - Lucas Zoroddu; Pierre Humbert; Laurent Oudre (EUSIPCO, 2024)

Learning Network Granger causality using Graph Prior Knowledge. - Lucas Zoroddu; Pierre Humbert; Laurent Oudre (Trans. Mach. Learn. Res., 2024)

Transductive Conformal Inference for Ranking. - Jean-Baptiste Fermanian; Pierre Humbert; Gilles Blanchard (CoRR, 2025)

On Volume Minimization in Conformal Regression. - Batiste Le Bars; Pierre Humbert (CoRR, 2025)