15 citations · 19 across the 6 of their papers we have counts for
6 papers
Effective regions and kernels in continuous sparse regularisation, with application to sketched mixtures
Yohann De Castro, Rémi Gribonval, Nicolas Jouvin
This paper advances the general theory of continuous sparse regularisation on measures with the Beurling-LASSO (BLASSO). This TV-regularised convex program on the space of measures…
jinns: a JAX Library for Physics-Informed Neural Networks
Hugo Gangloff, Nicolas Jouvin
jinns is an open-source Python library for physics-informed neural networks, built to tackle both forward and inverse problems, as well as meta-model learning. Rooted in the JAX ec…
greed: An R Package for Model-Based Clustering by Greedy Maximization of the Integrated Classification Likelihood
Etienne Côme, Nicolas Jouvin
The greed package implements the general and flexible framework of arXiv:2002.11577 for model-based clustering in the R language. Based on the direct maximization of the exact Inte…
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering
Nicolas Jouvin, Charles Bouveyron, Pierre Latouche
High-dimensional data clustering has become and remains a challenging task for modern statistics and machine learning, with a wide range of applications. We consider in this work t…
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood
Etienne Côme, Nicolas Jouvin, Pierre Latouche +1
Finding a set of nested partitions of a dataset is useful to uncover relevant structure at different scales, and is often dealt with a data-dependent methodology. In this paper, we…
Greedy clustering of count data through a mixture of multinomial PCA
Nicolas Jouvin, Pierre Latouche, Charles Bouveyron +2
Count data is becoming more and more ubiquitous in a wide range of applications, with datasets growing both in size and in dimension. In this context, an increasing amount of work…