33 citations · 82 across the 16 of their papers we have counts for
19 papers
TraitLab: a Matlab package for fitting and simulating binary tree-like data
Luke J. Kelly, Geoff K. Nicholls, Robin J. Ryder +1
TraitLab is a software package for simulating, fitting and analysing tree-like binary data under a stochastic Dollo model of evolution. The model also allows for rate heterogeneity…
Bayesian Inference for Vertex-Series-Parallel Partial Orders
Chuxuan, Jiang, Geoff K. Nicholls +1
Partial orders are a natural model for the social hierarchies that may constrain "queue-like" rank-order data. However, the computational cost of counting the linear extensions of…
Biclustering random matrix partitions with an application to classification of forensic body fluids
Chieh-Hsi Wu, Amy D. Roeder, Geoff K. Nicholls
Classification of unlabeled data is usually achieved by supervised learning from labeled samples. Although there exist many sophisticated supervised machine learning methods that c…
Bayesian inference for partial orders from random linear extensions: power relations from 12th Century Royal Acta
Geoff K. Nicholls, Jeong Eun Lee, Nicholas Karn +3
In the eleventh and twelfth centuries in England, Wales and Normandy, Royal Acta were legal documents in which witnesses were listed in order of social status. Any bishops present…
Scalable Semi-Modular Inference with Variational Meta-Posteriors
Chris U. Carmona, Geoff K. Nicholls
The Cut posterior and related Semi-Modular Inference are Generalised Bayes methods for Modular Bayesian evidence combination. Analysis is broken up over modular sub-models of the j…
Valid belief updates for prequentially additive loss functions arising in Semi-Modular Inference
Geoff K. Nicholls, Jeong Eun Lee, Chieh-Hsi Wu +1
Model-based Bayesian evidence combination leads to models with multiple parameteric modules. In this setting the effects of model misspecification in one of the modules may in some…