François Caron | DeepAI

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∙ 02/02/2023

Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning

We consider the optimisation of large and shallow neural networks via gr...

0 François Caron, et al. ∙

∙ 05/17/2022

Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility

This article studies the infinite-width limit of deep feedforward neural...

29 Hoil Lee, et al. ∙

∙ 07/02/2021

Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification

This article studies the asymptotic properties of Bayesian or frequentis...

0 Zacharie Naulet, et al. ∙

∙ 06/19/2020

The Normal-Generalised Gamma-Pareto process: A novel pure-jump Lévy process with flexible tail and jump-activity properties

Pure-jump Lévy processes are popular classes of stochastic processes whi...

0 Fadhel Ayed, et al. ∙

∙ 03/30/2020

Non-exchangeable feature allocation models with sublinear growth of the feature sizes

Feature allocation models are popular models used in different applicati...

1 Giuseppe Di Benedetto, et al. ∙

∙ 10/21/2019

Sparse Networks with Core-Periphery Structure

We propose a statistical model for graphs with a core-periphery structur...

0 Cian Naik, et al. ∙

∙ 05/26/2019

A unified construction for series representations and finite approximations of completely random measures

Infinite-activity completely random measures (CRMs) have become importan...

0 Juho Lee, et al. ∙

∙ 02/27/2019

Nonnegative Bayesian nonparametric factor models with completely random measures for community detection

We present a Bayesian nonparametric Poisson factorization model for mode...

0 Fadhel Ayed, et al. ∙

∙ 02/13/2019

Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior

Bayesian nonparametric approaches, in particular the Pitman-Yor process ...

0 Fadhel Ayed, et al. ∙

∙ 10/03/2018

A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure

We consider a non-projective class of inhomogeneous random graph models ...

0 Juho Lee, et al. ∙

∙ 03/16/2018

Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data

We propose a novel class of network models for temporal dyadic interacti...

0 Xenia Miscouridou, et al. ∙

∙ 11/20/2017

Non-exchangeable random partition models for microclustering

Many popular random partition models, such as the Chinese restaurant pro...

0 Giuseppe Di Benedetto, et al. ∙

∙ 02/14/2017

Sequential Dirichlet Process Mixtures of Multivariate Skew t-distributions for Model-based Clustering of Flow Cytometry Data

Flow cytometry is a high-throughput technology used to quantify multiple...

0 Boris P. Hejblum, et al. ∙

∙ 07/06/2016

Bayesian nonparametrics for Sparse Dynamic Networks

We propose a Bayesian nonparametric prior for time-varying networks. To ...

0 Konstantina Palla, et al. ∙

∙ 02/09/2016

Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm

Unsupervised image segmentation aims at clustering the set of pixels of ...

0 Richard Yi Da Xu, et al. ∙

∙ 02/05/2016

Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities

We propose a novel statistical model for sparse networks with overlappin...

0 Adrien Todeschini, et al. ∙

∙ 01/06/2014

Sparse graphs using exchangeable random measures

Statistical network modeling has focused on representing the graph as a ...

0 François Caron, et al. ∙

∙ 11/21/2012

Bayesian nonparametric Plackett-Luce models for the analysis of preferences for college degree programmes

In this paper we propose a Bayesian nonparametric model for clustering p...

0 François Caron, et al. ∙

∙ 11/19/2012

Bayesian nonparametric models for ranked data

We develop a Bayesian nonparametric extension of the popular Plackett-Lu...

0 François Caron, et al. ∙

∙ 03/01/2012

Sparsity-Promoting Bayesian Dynamic Linear Models

Sparsity-promoting priors have become increasingly popular over recent y...

0 François Caron, et al. ∙

∙ 11/08/2010

Efficient Bayesian Inference for Generalized Bradley-Terry Models

The Bradley-Terry model is a popular approach to describe probabilities ...

0 François Caron, et al. ∙

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