Kernel-Based Testing for Single-Cell Differential Analysis

1 code implementation • 17 Jul 2023 • Anthony Ozier-Lafontaine, Camille Fourneaux, Ghislain Durif, Polina Arsenteva, Céline Vallot, Olivier Gandrillon, Sandrine Giraud, Bertrand Michel, Franck Picard

Single-cell technologies offer insights into molecular feature distributions, but comparing them poses challenges.

Benchopt: Reproducible, efficient and collaborative optimization benchmarks

3 code implementations • 27 Jun 2022 • Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré La Tour, Ghislain Durif, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoit Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter

Numerical validation is at the core of machine learning research as it allows to assess the actual impact of new methods, and to confirm the agreement between theory and practice.

Benchmarking Image Classification +1

Kernel Operations on the GPU, with Autodiff, without Memory Overflows

no code implementations • 27 Mar 2020 • Benjamin Charlier, Jean Feydy, Joan Alexis Glaunès, François-David Collin, Ghislain Durif

The KeOps library provides a fast and memory-efficient GPU support for tensors whose entries are given by a mathematical formula, such as kernel and distance matrices.

Probabilistic Count Matrix Factorization for Single Cell Expression Data Analysis

2 code implementations • 30 Oct 2017 • Ghislain Durif, Laurent Modolo, Jeff E. Mold, Sophie Lambert-Lacroix, Franck Picard

First, the expression dynamics (gene to gene variability) can be quantified more accurately, thanks to the measurement of lowly-expressed genes.

Methodology