Geneviève Robin | DeepAI

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∙ 02/23/2023

A Statistical Learning Take on the Concordance Index for Survival Analysis

The introduction of machine learning (ML) techniques to the field of sur...

0 Alex Nowak-Vila, et al. ∙

∙ 05/05/2022

Generative methods for sampling transition paths in molecular dynamics

Molecular systems often remain trapped for long times around some local ...

0 Tony Lelièvre, et al. ∙

∙ 02/11/2022

Inference of Multiscale Gaussian Graphical Model

Gaussian Graphical Models (GGMs) are widely used for exploratory data an...

0 Do Edmond Sanou, et al. ∙

∙ 11/03/2021

Federated Expectation Maximization with heterogeneity mitigation and variance reduction

The Expectation Maximization (EM) algorithm is the default algorithm for...

0 Aymeric Dieuleveut, et al. ∙

∙ 08/17/2021

Technical report: Impact of evaluation metrics and sampling on the comparison of machine learning methods for biodiversity indicators prediction

Machine learning (ML) approaches are used more and more widely in biodiv...

0 Geneviève Robin, et al. ∙

∙ 11/29/2019

Link Prediction in the Stochastic Block Model with Outliers

The Stochastic Block Model is a popular model for network analysis in th...

0 Solenne Gaucher, et al. ∙

∙ 12/20/2018

Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames

Many applications of machine learning involve the analysis of large data...

0 Geneviève Robin, et al. ∙

∙ 06/26/2018

Main effects and interactions in mixed and incomplete data frames

A mixed data frame (MDF) is a table collecting categorical, numerical an...

0 Geneviève Robin, et al. ∙

∙ 04/30/2018

Imputation of mixed data with multilevel singular value decomposition

Statistical analysis of large data sets offers new opportunities to bett...

0 François Husson, et al. ∙

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