4 citations · 10 across the 11 of their papers we have counts for
11 papers
Bessel-Debiased Pseudo-Marginal MCMC for Generalised Bayesian Inference
Yingkai Lu, Jeong Eun Lee, Geoff K. Nicholls
Generalised Bayesian inference uses weights of the form even when the loss is only estimated. Exponentiating an unbiased loss estimate changes the target, a…
Hierarchical Partial-Order Models for Ranking
Dongqing Li, Geoff K. Nicholls, Jeong Eun Lee +2
Rank aggregation combines information from ordered lists ranking items by preference. Classical parametric models for such data, including the Mallows and Plackett-Luce models, ass…
Logistic Gaussian process density regression: a generalized Bayesian approach
Zichuan Chen, Lucas Kock, Jeong Eun Lee +1
Density regression extends conventional parametric regression by allowing the entire distribution of the response to vary flexibly with covariates rather than just low-order moment…
Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation
Shiyi Sun, Geoff K. Nicholls, Jeong Eun Lee
Generalized Bayesian Inference (GBI) tempers a loss with a temperature to mitigate overconfidence and improve robustness under model misspecification, but existing GBI metho…
Bayesian inference for the learning rate in Generalised Bayesian inference
Jeong Eun Lee, Sitong Liu, Geoff K. Nicholls
In Generalised Bayesian Inference (GBI), the learning rate and hyperparameters of the loss must be estimated. These inference-hyperparameters can't be estimated jointly with the ot…
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…
A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series
Yixuan Liu, Claudia Kirch, Jeong Eun Lee +1
This paper presents a novel approach to Bayesian nonparametric spectral analysis of stationary multivariate time series. Starting with a parametric vector-autoregressive model, the…
Bayesian nonparametric spectral analysis of locally stationary processes
Yifu Tang, Claudia Kirch, Jeong Eun Lee +1
Based on a novel dynamic Whittle likelihood approximation for locally stationary processes, a Bayesian nonparametric approach to estimating the time-varying spectral density is pro…
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…
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…
Bayesian threshold selection for extremal models using measures of surprise
J. Lee, Y. Fan, S. A. Sisson
Statistical extreme value theory is concerned with the use of asymptotically motivated models to describe the extreme values of a process. A number of commonly used models are vali…