18 citations · 20 across the 5 of their papers we have counts for
5 papers
Increasing trust in new data sources: crowdsourcing image classification for ecology
Edgar Santos-Fernandez, Julie Vercelloni, Aiden Price +4
Crowdsourcing methods facilitate the production of scientific information by non-experts. This form of citizen science (CS) is becoming a key source of complementary data in many f…
Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics
Joshua J. Bon, Adam Bretherton, Katie Buchhorn +12
Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most sta…
A Bayesian latent allocation model for clustering compositional data with application to the Great Barrier Reef
Luiza Piancastelli, Nial Friel, Julie Vercelloni +2
Relative abundance is a common metric to estimate the composition of species in ecological surveys reflecting patterns of commonness and rarity of biological assemblages. Measureme…
Correcting misclassification errors in crowdsourced ecological data: A Bayesian perspective
Edgar Santos-Fernandez, Erin E. Peterson, Julie Vercelloni +2
Many research domains use data elicited from "citizen scientists" when a direct measure of a process is expensive or infeasible. However, participants may report incorrect estimate…
Monitoring through many eyes: Integrating disparate datasets to improve monitoring of the Great Barrier Reef
Erin E Peterson, Edgar Santos-Fernández, Carla Chen +13
Numerous organisations collect data in the Great Barrier Reef (GBR), but they are rarely analysed together due to different program objectives, methods, and data quality. We develo…