9 citations · 19 across the 16 of their papers we have counts for
4 papers · 2 filters
Flexible Transformations for Bayesian Score Calibration
Adam Bretherton, Joshua J. Bon, David J. Warne +2
Modern statistical models are growing increasingly complex in an effort to realistically capture system dynamics. Using standard simulation-based inference, these models may be com…
-PSD: Scalable Approximate SNR-Optimised Polynomial Stein Discrepancies
Minh-Long Nguyen, Thanh-Long Vu, Christopher Drovandi +2
Polynomial Stein discrepancies (PSD) provide a scalable alternative to kernel Stein methods for measuring sample quality and goodness-of-fit testing, but their statistical properti…
Hierarchical Bayes meets hierarchical forecasting: A flexible framework for level-focused forecasts
Arwen Nugteren, Mahdi Abolghasemi, Kerrie Mengersen +1
Decision-making in hierarchical systems requires probabilistic forecasts at all cross-sectional levels. Current hierarchical forecasting methods typically generate independent fore…
Bayesian inference for ordinary differential equations models with heteroscedastic measurement error
Selva Salimi, David J. Warne, Christopher Drovandi
Ordinary differential equation (ODE) models are widely used to describe systems in many areas of science. To ensure these models provide accurate and interpretable representations…