13 citations · 20 across the 8 of their papers we have counts for
4 papers · 1 filter
Amortized Variational Inference of Latent Intensities from Replicated Point Patterns
Wenqing Liu, Xenia Miscouridou, Déborah Sulem
Bayesian inference for latent point process intensities often relies on per-dataset sampling or optimization, making repeated inference computationally expensive. We propose a neur…
Fair Variable Selection
Deborah Sulem, Jack Jewson
Algorithms are increasingly being used to help automate and improve data-driven decisions, but care must be taken to prevent such algorithms from learning discriminatory patterns f…
Flexible and Scalable Bayesian Modelling of Spatio-Temporal Hawkes Processes
Wenqing Liu, Xenia Miscouridou, Déborah Sulem
Existing spatio-temporal Hawkes process models typically rely on either parametric or semiparametric assumptions, limiting the model's ability to capture complex endogenous and exo…
Posterior concentration in spatio-temporal Hawkes processes
Xenia Miscouridou, Deborah Sulem
We develop a Bayesian nonparametric framework for inference in spatio-temporal Hawkes processes, extending existing theoretical results beyond the purely temporal setting. Our fram…