Ambroise C

Latest

• Mixture of multilayer stochastic block models for multiview clustering
• Holistic view of the seascape dynamics and environment impact on macro-scale genetic connectivity of marine plankton populations
• Inference of Multiscale Gaussian Graphical Model
• A Sparse Mixture-of-Experts Model With Screening of Genetic Associations to Guide Disease Subtyping
• Compression structur{e}e de l'information g{e}n{e}tique et {e}tude d'association pang{e}nomique par mod{e}les additifs
• Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process
• AI-based mobile application for antibiotic resistance testing
• Accounting for missing actors in interaction network inference from abundance data
• How marine currents and environment shape plankton genomic differentiation: a mosaic view from Tara oceans metagenomic data
• Tree-based Inference of Species Interaction Networks from Abundance Data
• Exploring the link between additive heritability and prediction accuracy from a ridge regression perspective
• Fast computation of genome-metagenome interaction effects
• High heritability does not imply accurate prediction under the small additive effects hypothesis
• Incorporating phylogenetic information in microbiome differential abundance studies has no effect on detection power and FDR control
• Investigating population-scale allelic differential expression in wild populations of Oithona similis (Cyclopoida, Claus, 1866)
• metaVaR: introducing metavariant species models for reference-free metagenomic-based population genomics
• A generalized statistical framework to assess mixing ability from incomplete mixing designs using binary or higher order variety mixtures and application to wheat
• Adjacency-constrained hierarchical clustering of a band similarity matrix with application to genomics
• Applications in Genomics
• Incomplete graphical model inference via latent tree aggregation
• Systematic analysis of TruSeq, SMARTer and SMARTer Ultra-Low RNA-seq kits for standard, low and ultra-low quantity samples
• Epigenetics in forest trees: state of the art and potential implications for breeding and management in a context of climate change
• Estimation of mixing ability for variety mixtures: Statistical models and experimental results
• Learning the optimal scale for GWAS through hierarchical SNP aggregation
• Quantify Genomic Heritability Through a Prediction Measure
• Beyond support in two-stage variable selection
• Eigen-epistasis for detecting gene-gene interactions
• Estimating Narrow-Sense Heritability with Ridge Regression
• Quantify Genomic Heritability Through a Prediction Measure
• A greedy great approach to learn with complementary structured datasets
• AB0004 Characterization of Putative Pre-RA Signatures by Transcriptome Analysis
• Performance of a blockwise approach in variable selection using linkage disequilibrium information
• Significance testing for variable selection in high-dimension
• Model selection in overlapping stochastic block models
• Overlapping clustering methods for networks
• BP 529 F-60205 Compi{e}gne cedea-France
• Incorporating linkage disequilibrium blocks in Genome-Wide Association Studies
• Clustering by maximizing a fuzzy
• Sparsity by Worst-Case Penalties
• Variational Bayesian inference and complexity control for stochastic block models
• Accounting for population stratification in practice: a comparison of the main strategies dedicated to genome-wide association studies
• Defining a robust biological prior from pathway analysis to drive network inference
• Inferring multiple graphical structures
• New consistent and asymptotically normal parameter estimates for random-graph mixture models
• Overlapping stochastic block models with application to the french political blogosphere
• Clustering based on random graph model embedding vertex features
• New consistent and asymptotically normal estimators for random graph mixture models
• Strategies for online inference of model-based clustering in large and growing networks
• Weighted-LASSO for structured network inference from time course data
• Bayesian methods for graph clustering
• Inferring sparse Gaussian graphical models with latent structure
• Overlapping stochastic block models
• Simone: Statistical inference for modular networks
• Spatial Data Clustering
• Fast online graph clustering via Erdos--R{e}nyi mixture
• Identification of functional modules based on transcriptional regulation structure
• Strategies for online inference of network mixture
• An online classification EM algorithm based on the mixture model
• Parsimonious additive models
• A classification EM algorithm for binned data
• A Content-Based Image Retrieval System for Osteo-Articular Applications
• Driving Hierarchy Construction via Supervised Learning: Application to Osteo-Articular Medical Images Database
• Feature selection in robust clustering based on Laplace mixture
• Selection bias in working with the top genes in supervised classification of tissue samples
• Supervised learning for guiding hierarchy construction: Application to osteo-articular medical images database
• A decision tree classifier for vehicle failure isolation
• A mixture model-based on-line CEM algorithm
• Analyse de Donn{e}es et Data Mining
• Analyzing microarray gene expression data
• Discrimination par mod{e}les additifs parcimonieux
• Model selection via penalization in the additive Cox model
• P{e}nalisation l1 pour les MAG
• Pattern recognition method for off-board automotive vehicle failure isolation
• Use of Micro Array Data via Model-based Classification in the Study and Prediction of Survival from Lung Cancer
• A mixture model approach for on-line clustering
• G{e}n{e}ralisation du lasso aux modeles additifs
• Microarrays in gene expression studies
• Mixture model approach for acoustic emission control of pressure equipment
• On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples
• Penalized additive logistic regression for cardiovascular risk prediction
• A mixture model approach for binned data clustering
• Feature selection for semisupervised learning applied to image retrieval
• Image retrieval using mixture models and em algorithm
• Regularization methods for additive models
• A Semi-supervised Learning Approach to Image Retrieval
• Clustering and Models
• Selection bias in gene extraction on the basis of microarray gene-expression data
• Boosting mixture models for semi-supervised learning
• Learning from an imprecise teacher: probabilistic and evidential approaches
• Prediction of ozone peaks by mixture models
• Semi-supervised marginboost
• Semi-supervised marginboost
• Clustering by maximizing a fuzzy classification maximum likelihood criterion
• EM algorithm for partially known labels
• Hierarchical clustering of self-organizing maps for cloud classification
• An iterative algorithm for spatial clustering
• Convergence of an EM-type algorithm for spatial clustering
• The EM Algorithm and Extensions, by GM McLachlan and T. Krishnan
• Clustering of spatial data by the EM algorithm
• Analyzing dissimilarity matrices via Kohonen maps
• Approche probabiliste en classification automatique et contraintes de voisinage
• Constrained clustering and Kohonen self-organizing maps