4 papers
Extending confidence calibration to generalised measures of variation
Andrew Thompson, Vivek Desai
We propose the Variation Calibration Error (VCE) metric for assessing the calibration of machine learning classifiers. The metric can be viewed as an extension of the well-known Ex…
Evaluating the trustworthiness of the Fréchet Inception Distance with stochastic embedding representations
Ciaran Bench, Vivek Desai, Carlijn Roozemond +2
Feature embeddings acquired from pretrained models are widely used in medical applications of deep learning to assess the characteristics of datasets; e.g. to determine the quality…
A systematic evaluation of uncertainty quantification techniques in deep learning: a case study in photoplethysmography signal analysis
Ciaran Bench, Oskar Pfeffer, Vivek Desai +7
In principle, deep learning models trained on medical time-series, including wearable photoplethysmography (PPG) sensor data, can provide a means to continuously monitor physiologi…
Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks
Ciaran Bench, Vivek Desai, Mohammad Moulaeifard +3
Photoplethysmography (PPG) signals encode information about relative changes in blood volume that can be used to assess various aspects of cardiac health non-invasively, e.g.\ to d…