18 citations · 20 across the 4 of their papers we have counts for
4 papers
Bayesian Design for Sampling Anomalous Spatio-Temporal Data
Katie Buchhorn, Kerrie Mengersen, Edgar Santos-Fernandez +1
Data collected from arrays of sensors are essential for informed decision-making in various systems. However, the presence of anomalies can compromise the accuracy and reliability…
Graph Neural Network-Based Anomaly Detection for River Network Systems
Katie Buchhorn, Edgar Santos-Fernandez, Kerrie Mengersen +1
Water is the lifeblood of river networks, and its quality plays a crucial role in sustaining both aquatic ecosystems and human societies. Real-time monitoring of water quality is i…
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…
Bayesian Design with Sampling Windows for Complex Spatial Processes
Katie Buchhorn, Kerrie Mengersen, Edgar Santos-Fernandez +2
Optimal design facilitates intelligent data collection. In this paper, we introduce a fully Bayesian design approach for spatial processes with complex covariance structures, like…