2 papers
cs.SI2025
Approximate Bayesian Inference on Mechanisms of Network Growth and Evolution
Maxwell H Wang, Till Hoffmann, Jukka-Pekka Onnela
Mechanistic models can provide an intuitive and interpretable explanation of network growth by specifying a set of generative rules. These rules can be defined by domain knowledge…
stat.ME2025
Bayesian Inference for Sexual Contact Networks Using Longitudinal Survey Data
Till Hoffmann, Jukka-Pekka Onnela
Characterizing sexual contact networks is essential for understanding sexually transmitted infections, but principled parameter inference for mechanistic network models remains cha…