Lewis Smith

TL;DR: In this article, failure modes for MC dropout, a widely used approach for estimating uncertainty in deep models, are highlighted, and a proposal to improve the quality of uncertainty estimates using probabilistic model ensembles is made.

TL;DR: Overall, the field of late stage nucleophilic C-H fluorination has progressed much more slowly, a state of play explaining why C- H 18F-fluorination is still in its infancy.

TL;DR: By combining human and machine intelligence, Galaxy Zoo will be able to classify surveys of any conceivable scale on a timescale of weeks, providing massive and detailed morphology catalogues to support research into galaxy evolution.

TL;DR: DUQ as discussed by the authors is a deterministic deep model that can find and reject out-of-distribution data points at test time with a single forward pass, based on the idea of RBF networks.

TL;DR: A new BDL benchmark with a diverse set of tasks, inspired by a real-world medical imaging application on diabetic retinopathy diagnosis, and a systematic comparison of well-tuned BDL techniques on the various tasks concludes that some current techniques which solve benchmarks such as UCI `overfit' their uncertainty to the dataset underperform on this benchmark.