Nial Friel

Orcid: 0000-0003-4778-0254

Affiliations:
  • University College Dublin, Ireland


According to our database1, Nial Friel authored at least 34 papers between 1999 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference.
J. Comput. Graph. Stat., April, 2023

2022
Statistical Network Analysis with Bergm.
J. Stat. Softw., 2022

2019
Informed sub-sampling MCMC: approximate Bayesian inference for large datasets.
Stat. Comput., 2019

2018
Actor-Based Models for Longitudinal Networks.
Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Optimal Bayesian estimators for latent variable cluster models.
Stat. Comput., 2018

Choosing the number of groups in a latent stochastic blockmodel for dynamic networks.
Netw. Sci., 2018

Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo.
Comput. Stat. Data Anal., 2018

2017
Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution.
Soc. Networks, 2017

Investigation of the widely applicable Bayesian information criterion.
Stat. Comput., 2017

Inferring structure in bipartite networks using the latent blockmodel and exact ICL.
Netw. Sci., 2017

Bayesian model selection for the latent position cluster model for social networks.
Netw. Sci., 2017

2016
Bayesian exponential random graph models with nodal random effects.
Soc. Networks, 2016

Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels.
Stat. Comput., 2016

Properties of latent variable network models.
Netw. Sci., 2016

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

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

Efficient model selection for probabilistic K nearest neighbour classification.
Neurocomputing, 2015

Evaluating squat performance with a single inertial measurement unit.
Proceedings of the 12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, 2015

Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Actor-Based Models for Longitudinal Networks.
Encyclopedia of Social Network Analysis and Mining, 2014

Improving power posterior estimation of statistical evidence.
Stat. Comput., 2014

A generalized multiple-try version of the Reversible Jump algorithm.
Comput. Stat. Data Anal., 2014

2013
Bayesian model selection for exponential random graph models.
Soc. Networks, 2013

Improved Bayesian inference for the stochastic block model with application to large networks.
Comput. Stat. Data Anal., 2013

Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification
CoRR, 2013

2012
Block clustering with collapsed latent block models.
Stat. Comput., 2012

Tuning tempered transitions.
Stat. Comput., 2012

Model-based clustering in networks with Stochastic Community Finding
CoRR, 2012

Bayesian inference for gibbs random fields using composite likelihoods.
Proceedings of the Winter Simulation Conference, 2012

2011
Bayesian inference for exponential random graph models.
Soc. Networks, 2011

Classification using distance nearest neighbours.
Stat. Comput., 2011

2010
A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Deterministic Bayesian inference for the p* model.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

1999
A new thresholding technique based on random sets.
Pattern Recognit., 1999


  Loading...