2 papers
stat.ME2026
Gradient-Based Approximate Bayesian Inference with Entropy-Optimized Summary Statistics for Compartmental Models
Xiahui Li, Fergus J. Chadwick, Ben Swallow
Recent pandemics have highlighted the critical role of infectious disease models in guiding public health decision-making, driving demand for realistic models that can provide time…
stat.ME2025
Advances in Approximate Bayesian Inference for Models in Epidemiology
Xiahui Li, Fergus Chadwick, Ben Swallow
Bayesian inference methods are useful in infectious diseases modeling due to their capability to propagate uncertainty, manage sparse data, incorporate latent structures, and addre…