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Found 7 papers, 4 papers with code
Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes
Here we develop a new class of spatiotemporal Hawkes processes that can capture both triggering and clustering behavior and we provide an efficient method for performing inference.
Unifying incidence and prevalence under a time-varying general branching process
We also show that the incidence integral equations that arise from both of these specific models agree with the renewal equation used ubiquitously in infectious disease modelling.
Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting
An important example of this problem is the nowcasting of COVID-19 mortality: given a stream of reported counts of daily deaths, can we correct for the delays in reporting to paint an accurate picture of the present, with uncertainty?
Relaxed-Responsibility Hierarchical Discrete VAEs
Successfully training Variational Autoencoders (VAEs) with a hierarchy of discrete latent variables remains an area of active research.
A unified construction for series representations and finite approximations of completely random measures
In particular, we show that one can get novel series representations for the generalized gamma process and the stable beta process.
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data
We propose a novel class of network models for temporal dyadic interaction data.
Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities
We propose a novel statistical model for sparse networks with overlapping community structure.
