5 papers
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 meth…
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 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…