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…
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…
Approximate Inference for Longitudinal Mechanistic HIV Contact Networks
Octavious Smiley, Till Hoffmann, Jukka-Pekka Onnela
Network models are increasingly used to study infectious disease spread. Exponential Random Graph models have a history in this area, with scalable inference methods now available.…
Network Layout Algorithm with Covariate Smoothing
Octavious Smiley, Till Hoffmann, Jukka-Pekka Onnela
Network science explores intricate connections among objects, employed in diverse domains like social interactions, fraud detection, and disease spread. Visualization of networks f…