A new thresholding technique based on random sets. - Nial Friel; Ilya S. Molchanov (Pattern Recognit., 1999)

Deterministic Bayesian inference for the p* model. - Haakon Michael Austad; Nial Friel (AISTATS, 2010)

A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection. - Silvia Pandolfi; Francesco Bartolucci; Nial Friel (AISTATS, 2010)

Classification using distance nearest neighbours. - Nial Friel; Anthony N. Pettitt (Stat. Comput., 2011)

Bayesian inference for exponential random graph models. - Alberto Caimo; Nial Friel (Soc. Networks, 2011)

Bayesian inference for gibbs random fields using composite likelihoods. - Nial Friel (WSC, 2012)

Model-based clustering in networks with Stochastic Community Finding - Aaron F. McDaid; Thomas Brendan Murphy; Nial Friel; Neil J. Hurley (CoRR, 2012)

Tuning tempered transitions. - Gundula Behrens; Nial Friel; Merrilee Hurn (Stat. Comput., 2012)

Block clustering with collapsed latent block models. - Jason Wyse; Nial Friel (Stat. Comput., 2012)

Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification - Ji Won Yoon; Nial Friel (CoRR, 2013)

Improved Bayesian inference for the stochastic block model with application to large networks. - Aaron F. McDaid; Thomas Brendan Murphy; Nial Friel; Neil J. Hurley (Comput. Stat. Data Anal., 2013)

Bayesian model selection for exponential random graph models. - Alberto Caimo; Nial Friel (Soc. Networks, 2013)

A generalized multiple-try version of the Reversible Jump algorithm. - Silvia Pandolfi; Francesco Bartolucci; Nial Friel (Comput. Stat. Data Anal., 2014)

Improving power posterior estimation of statistical evidence. - Nial Friel; Merrilee Hurn; Jason Wyse (Stat. Comput., 2014)

Actor-Based Models for Longitudinal Networks. - Alberto Caimo; Nial Friel (Encyclopedia of Social Network Analysis and Mining, 2014)

Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields. - Julien Stoehr; Nial Friel (AISTATS, 2015)

Evaluating squat performance with a single inertial measurement unit. - Martin O'Reilly 001; Darragh Whelan; Charalampos Chanialidis; Nial Friel; Eamonn Delahunt; Tomás Ward; Brian Caulfield 001 (BSN, 2015)

Efficient model selection for probabilistic K nearest neighbour classification. - Ji Won Yoon; Nial Friel (Neurocomputing, 2015)

Introduction to "Pre-processing for approximate Bayesian computation in image analysis" by M. Moores, C. Drovandi, K. Mengersen, C. Robert. - Nial Friel (Stat. Comput., 2015)

Introduction to "Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks" by A. Caimo, A. Mira. - Nial Friel (Stat. Comput., 2015)

Properties of latent variable network models. - Riccardo Rastelli; Nial Friel; Adrian E. Raftery (Netw. Sci., 2016)

Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels. - Pierre Alquier; Nial Friel; Richard G. Everitt; Aidan Boland (Stat. Comput., 2016)

Bayesian exponential random graph models with nodal random effects. - Stephanie Thiemichen; Nial Friel; Alberto Caimo; Göran Kauermann (Soc. Networks, 2016)

Bayesian model selection for the latent position cluster model for social networks. - Caitríona Ryan; Jason Wyse; Nial Friel (Netw. Sci., 2017)

Inferring structure in bipartite networks using the latent blockmodel and exact ICL. - Jason Wyse; Nial Friel; Pierre Latouche (Netw. Sci., 2017)

Investigation of the widely applicable Bayesian information criterion. - Nial Friel; James P. McKeone; Chris J. Oates; Anthony N. Pettitt (Stat. Comput., 2017)

Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution. - Lampros Bouranis; Nial Friel; Florian Maire (Soc. Networks, 2017)

Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo. - Lampros Bouranis; Nial Friel; Florian Maire (Comput. Stat. Data Anal., 2018)

Choosing the number of groups in a latent stochastic blockmodel for dynamic networks. - Riccardo Rastelli; Pierre Latouche; Nial Friel (Netw. Sci., 2018)

Optimal Bayesian estimators for latent variable cluster models. - Riccardo Rastelli; Nial Friel (Stat. Comput., 2018)

Actor-Based Models for Longitudinal Networks. - Alberto Caimo; Nial Friel (Encyclopedia of Social Network Analysis and Mining. 2nd Ed., 2018)

Informed sub-sampling MCMC: approximate Bayesian inference for large datasets. - Florian Maire; Nial Friel; Pierre Alquier (Stat. Comput., 2019)

Statistical Network Analysis with Bergm. - Alberto Caimo; Lampros Bouranis; Robert Krause; Nial Friel (J. Stat. Softw., 2022)

Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference. - Luiza S. C. Piancastelli; Nial Friel; Wagner Barreto-Souza; Hernando C. Ombao (J. Comput. Graph. Stat., 2023)

Bayesian testing of scientific expectations under exponential random graph models. - Joris Mulder; Nial Friel; Philip Leifeld (Soc. Networks, 2024)

The clustered Mallows model. - Luiza S. C. Piancastelli; Nial Friel (Stat. Comput., 2025)