1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
Accounting for contact network uncertainty in epidemic inferences
Maxwell H. Wang, Jukka-Pekka Onnela
When modeling the dynamics of infectious disease, the incorporation of contact network information allows for the capture of the non-randomness and heterogeneity of realistic conta…
Flexible Bayesian Inference on Partially Observed Epidemics
Maxwell H. Wang, Jukka-Pekka Onnela
Individual-based models of contagious processes are useful for predicting epidemic trajectories and informing intervention strategies. In such models, the incorporation of contact…
Leveraging Contact Network Information in Clustered Randomized Studies of Contagion Processes
Maxwell H Wang, Patrick Staples, Mélanie Prague +2
In a randomized study, leveraging covariates related to the outcome (e.g. disease status) may produce less variable estimates of the effect of exposure. For contagion processes ope…