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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...
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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...
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07/02/2021
Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification
This article studies the asymptotic properties of Bayesian or frequentis...
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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...
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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...
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10/21/2019
Sparse Networks with Core-Periphery Structure
We propose a statistical model for graphs with a core-periphery structur...
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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...
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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...
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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 ...
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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 ...
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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...
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11/20/2017
Non-exchangeable random partition models for microclustering
Many popular random partition models, such as the Chinese restaurant pro...
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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...
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07/06/2016
Bayesian nonparametrics for Sparse Dynamic Networks
We propose a Bayesian nonparametric prior for time-varying networks. To ...
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02/09/2016
Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm
Unsupervised image segmentation aims at clustering the set of pixels of ...
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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...
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01/06/2014
Sparse graphs using exchangeable random measures
Statistical network modeling has focused on representing the graph as a ...
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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...
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11/19/2012
Bayesian nonparametric models for ranked data
We develop a Bayesian nonparametric extension of the popular Plackett-Lu...
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03/01/2012
Sparsity-Promoting Bayesian Dynamic Linear Models
Sparsity-promoting priors have become increasingly popular over recent y...
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11/08/2010