40 citations · 133 across the 10 of their papers we have counts for
10 papers
A Probabilistic Graph Coupling View of Dimension Reduction
Hugues Van Assel, Thibault Espinasse, Julien Chiquet +1
Most popular dimension reduction (DR) methods like t-SNE and UMAP are based on minimizing a cost between input and latent pairwise similarities. Though widely used, these approache…
Minimax estimation of Functional Principal Components from noisy discretized functional data
Ryad Belhakem, Franck Picard, Vincent Rivoirard +1
Functional Principal Component Analysis is a reference method for dimension reduction of curve data. Its theoretical properties are now well understood in the simplified case where…
Uniform Deconvolution for Poisson Point Processes
Anna Bonnet, Claire Lacour, Franck Picard +1
We focus on the estimation of the intensity of a Poisson process in the presence of a uniform noise. We propose a kernel-based procedure fully calibrated in theory and practice. We…
Probabilistic Count Matrix Factorization for Single Cell Expression Data Analysis
Ghislain Durif, Laurent Modolo, Jeff E. Mold +2
The development of high throughput single-cell sequencing technologies now allows the investigation of the population level diversity of cellular transcriptomes. This diversity has…
Continuous testing for Poisson process intensities: A new perspective on scanning statistics
Franck Picard, Patricia Reynaud-Bouret, Etienne Roquain
We propose a novel continuous testing framework to test the intensities of Poisson Processes. This framework allows a rigorous definition of the complete testing procedure, from an…
Minimax wavelet estimation for multisample heteroscedastic non-parametric regression
Madison Giacofc, Sophie Lambert-Lacroix, Franck Picard
The problem of estimating the baseline signal from multisample noisy curves is investigated. We consider the functional mixed effects model, and we suppose that the functional fixe…
High Dimensional Classification with combined Adaptive Sparse PLS and Logistic Regression
G. Durif, L. Modolo, J. Michaelsson +3
Motivation: The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent over-optimistic predictions. This chal…
Adaptive Lasso and group-Lasso for functional Poisson regression
S. Ivanoff, F. Picard, V. Rivoirard
High dimensional Poisson regression has become a standard framework for the analysis of massive counts datasets. In this work we estimate the intensity function of the Poisson regr…
Spatially-constrained clustering of ecological networks
Vincent Miele, Franck Picard, Stéphane Dray
Spatial ecological networks are widely used to model interactions between georeferenced biological entities (e.g., populations or communities). The analysis of such data often lead…
Strategies for online inference of model-based clustering in large and growing networks
Hugo Zanghi, Franck Picard, Vincent Miele +1
In this paper we adapt online estimation strategies to perform model-based clustering on large networks. Our work focuses on two algorithms, the first based on the SAEM algorithm,…