5 papers
Scalable Bayesian Spatial Mixture Modelling for Remote Sensing Image Segmentation
Bao Khanh Nguyen, Iain Cameron, Cecilia Balocchi +1
Accurate and scalable land cover classification is essential for global conservation monitoring and policy-making. While remote sensing images provide a cost-effective alternative…
Partial Trace-Class Bayesian Neural Networks
Arran Carter, Torben Sell
Bayesian neural networks (BNNs) allow rigorous uncertainty quantification in deep learning, but often come at a prohibitive computational cost. We propose three different innovativ…
Nonparametric classification with missing data
Torben Sell, Thomas B. Berrett, Timothy I. Cannings
We introduce a new nonparametric framework for classification problems in the presence of missing data. The key aspect of our framework is that the regression function decomposes i…
Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-Differentiable Priors
Jacob Vorstrup Goldman, Torben Sell, Sumeetpal Sidhu Singh
The use of non-differentiable priors in Bayesian statistics has become increasingly popular, in particular in Bayesian imaging analysis. Current state of the art methods are approx…
Trace-class Gaussian priors for Bayesian learning of neural networks with MCMC
Torben Sell, Sumeetpal S. Singh
This paper introduces a new neural network based prior for real valued functions on which, by construction, is more easily and cheaply scaled up in the domain dimensi…