Probabilités et Statistiques

Apprentissage statistique Big Data Dynamic networks Interacting particle system Penalization Binary image Discretization scheme Quantization Variable selection Categorization Chunking Sparsity Convergence rate Unitary Events Level sets Convergence order Variational inference Exact ICL Bootstrap Clustering Diffusion process Stochastic block model Wasserstein diffusion Common noise Synchronization Propagation of chaos Gaussian fields Excursion sets Optimization BIC Sélection de modèle Distributed algorithms Model selection Thermal conductivity U-statistics Deconvolution Adaptive estimation Random graphs Adaptive tests Classification non supervisée Large deviations Neuroscience Coupling Slope heuristic Random environment Graphes Coalescing particles Plug-in estimation Concentration inequality Aggregation methods Fokker-Planck equation Regression Category learning Filtering Random forests Green-Kubo formula Anomalous heat transport Hawkes process Oracle inequalities Fluctuation relations Estimator selection Neurosciences Feynman-Kac measures Central limit theorems Resampling methods Crossings Thresholding rule Oracle inequality Lévy process Uniform separation rate Hidden Markov model Non-equilibrium systems Permutation Multiple testing AIC Hausdorff distance Homogenization Nonparametric estimation Centralité intermédiaire Co-clustering Deep learning FBSDEs Combinatorial enumeration Mixture models Design Interacting particle systems Model based clustering Local time Density estimation Cognition Latent block model Graphs Fourier's law Classification Discrete event simulation Geometric inference Point processes Graph theory Poisson process SEM-Gibbs algorithm