J. Arbel

发表

BAYESIAN NONPARAMETRIC DEPENDENT MODEL FOR THE STUDY OF DIVERSITY FOR SPECIES DATA

K. Mengersen, J. Rousseau, J. Arbel, 2014 .

Approximate Bayesian computation with surrogate posteriors

Florence Forbes, Julyan Arbel, Hien D. Nguyen, 2021 .

On the sub-Gaussianity of the Beta and Dirichlet distributions

J. Arbel, O. Marchal, Julyan Arbel, 2017, 1705.00048.

On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables

J. Arbel, O. Marchal, Hien Nguyen, 2019, ESAIM: Probability and Statistics.

15 Applications in Industry

Earl W. Duncan, K. Mengersen, J. Arbel, 2019 .

Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity

K. Mengersen, J. Rousseau, J. Arbel, 2014, 1402.3093.

Bayesian nonparametric inference for discovery probabilities: credible intervals and large sample asymptotics

Y. Teh, S. Favaro, J. Arbel, 2015, 1506.04915.

Inverse regression in MR Fingerprinting: reducing dictionary size while increasing parameters accuracy

Emmanuel L. Barbier, F. Forbes, J. Arbel, 2019 .

A Bayesian Nonparametric Approach to Ecological Risk Assessment

I. Prünster, J. Arbel, G. K. K. King, 2016 .

Contributions to Bayesian nonparametric statistic

J. Arbel, Julyan Arbel, 2013 .

On the Truncation Error of a Superposed Gamma Process

I. Prünster, J. Arbel, 2016 .

Bayesian Optimal Adaptive Estimation Using a Sieve Prior

Judith Rousseau, Julyan Arbel, Ghislaine Gayraud, 2012, 1204.2392.

Approximating Predictive Probabilities of Gibbs-Type Priors

S. Favaro, J. Arbel, 2017, Sankhya A.

A simple proof of Pitman–Yor’s Chinese restaurant process from its stick-breaking representation

J. Arbel, Caroline Lawless, 2018, Dependence Modeling.

Stochastic Approximations to the Pitman–Yor Process

I. Pruenster, J. Arbel, P. D. Blasi, 2018, Bayesian Analysis.

Clustering Milky Way’s Globulars: a Bayesian Nonparametric Approach

J. Arbel, 2019 .

On the Use of a Local Rˆ to Improve MCMC Convergence Diagnostic

S. Girard, J. Arbel, A. Dutfoy, 2023, Bayesian Analysis.

Latent factor models: a tool for dimension reduction in joint species distribution models

J. Arbel, W. Thuiller, D. Bystrova, 2022 .

Generalized Weibull-tail distributions

J. Arbel, M. Vladimirova, S. Girard, 2021 .

Cold Posteriors through PAC-Bayes

J. Arbel, Konstantinos Pitas, Julyan Arbel, 2022, ArXiv.

Beta and Dirichlet sub-Gaussianity

J. Arbel, O. Marchal, 2018 .

Comment on Article by Wade and Ghahramani

J. Arbel, R. Corradin, Michal Lewandowski, 2018 .

On the Hurwitz zeta function with an application to the beta-exponential distribution

J. Arbel, Bernardo Nipoti, O. Marchal, 2019, Journal of Inequalities and Applications.

On the interpretations of joint modelling in community ecology

J. Arbel, W. Thuiller, T. Münkemüller, 2022 .

Reparameterization of extreme value framework for improved Bayesian workflow

S. Girard, J. Arbel, A. Dutfoy, 2022, 2210.05224.

Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors

F. Forbes, J. Arbel, H. Nguyen, 2022, Statistics and Computing.

Truncation error of a superposed gamma process in a decreasing order representation

I. Prünster, J. Arbel, 2017, NIPS 2017.

Some distributional properties of Bayesian neural networks

Julyan Arbel, J. Arbel, 2018 .

Introduction to Bayesian nonparametric statistics

Julyan Arbel, J. Arbel, 2018 .

Bayesian mixture models (in)consistency for the number of clusters

J. Arbel, G. K. K. King, D. Bystrova, 2022, 2210.14201.

Bayesian nonparametric priors for hidden Markov random fields

F. Forbes, J. Arbel, Hongliang Lü, 2020, Statistics and Computing.

Gaussian Pre-Activations in Neural Networks: Myth or Reality?

J. Arbel, Pierre Wolinski, 2022, 2205.12379.

Multivariate expectile-based distribution: Properties, Bayesian inference, and applications

S. Girard, J. Arbel, H. Nguyen, 2022, Journal of Statistical Planning and Inference.

Bayesian mixture models (in)consistency for the number of clusters

J. Arbel, G. K. K. King, D. Bystrova, 2022, 2210.14201.

Dirichlet process mixtures under affine transformations of the data

J. Arbel, Bernardo Nipoti, R. Corradin, 2020, Computational Statistics.

Sequential Quasi Monte Carlo for Dirichlet Process Mixture Models

J. Arbel, J. Salomond, 2016, NIPS 2016.

Clustering Species With Residual Covariance Matrix in Joint Species Distribution Models

J. Arbel, A. Guglielmi, W. Thuiller, 2021, Frontiers in Ecology and Evolution.

Identifying and correcting for misspecifications in GWAS summary statistics and polygenic scores

J. Arbel, B. Vilhjálmsson, H. Aschard, 2022, bioRxiv.

LDpred2: better, faster, stronger

Bjarni J. Vilhjálmsson, Julyan Arbel, Florian Privé, 2020, bioRxiv.

Bayesian Survival Model based on Moment Characterization

A. Lijoi, J. Arbel, Bernardo Nipoti, 2015, 1506.05269.

Approximate Bayesian Computation Via the Energy Statistic

Florence Forbes, Julyan Arbel, Hien Duy Nguyen, 2019, IEEE Access.

Sub‐Weibull distributions: Generalizing sub‐Gaussian and sub‐Exponential properties to heavier tailed distributions

S. Girard, J. Arbel, M. Vladimirova, 2019, Stat.

BNPdensity: Bayesian nonparametric mixture modelling in R

J. Arbel, G. Kon Kam King, A. Lijoi, 2021, Australian & New Zealand Journal of Statistics.

Dirichlet process mixtures under affine transformations of the data

Julyan Arbel, Bernardo Nipoti, Riccardo Corradin, 2018, Comput. Stat..

BNPdensity: Bayesian nonparametric mixture modelling in R

A. Lijoi, I. Prünster, L. Nieto-Barajas, 2021 .

Understanding Priors in Bayesian Neural Networks at the Unit Level

Pablo Mesejo, Julyan Arbel, Jakob Verbeek, 2018, ICML.

On the Interpretations of Joint Modeling in Community Ecology.

J. Arbel, W. Thuiller, T. Münkemüller, 2021, Trends in ecology & evolution.

Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel-contaminated soil

K. Mengersen, J. Arbel, B. Raymond, 2015, Ecology and evolution.

Inferring disease architecture and predictive ability with LDpred2-auto

J. Arbel, B. Vilhjálmsson, B. Pasaniuc, 2023, bioRxiv.

Bayesian nonparametric priors for hidden Markov random fields

Julyan Arbel, Florence Forbes, Hongliang Lü, 2018, Stat. Comput..

Imposing Gaussian Pre-Activations in a Neural Network

J. Arbel, Pierre Wolinski, 2022, arXiv.org.

Bayesian neural network unit priors and generalized Weibull-tail property

Julyan Arbel, Mariia Vladimirova, St'ephane Girard, 2021, ACML.

Gaussian Pre-Activations in Neural Networks: Myth or Reality?

J. Arbel, Pierre Wolinski, Julyan Arbel, 2022, 2205.12379.

Bayesian block-diagonal graphical models via the Fiedler prior

J. Arbel, D. Bystrova, Mario Beraha, 2023 .