3 citations · 3 across the 4 of their papers we have counts for
4 papers
Existence-Field Diffusion Model for Spatial Point Processes with Variable Cardinality
Xiaoyin Pan, Christian R. Shelton, Rakshith Mahishi +1
We study generative modeling of spatial point processes (SPP), where both the number of points and their spatial configuration are governed by a joint distribution. While diffusion…
Variational Inference for Neyman-Scott Processes
Chengkuan Hong, Christian R. Shelton
Neyman-Scott processes (NSPs) have been applied across a range of fields to model points or temporal events with a hierarchy of clusters. Markov chain Monte Carlo (MCMC) is typical…
Deep Neyman-Scott Processes
Chengkuan Hong, Christian R. Shelton
A Neyman-Scott process is a special case of a Cox process. The latent and observable stochastic processes are both Poisson processes. We consider a deep Neyman-Scott process in thi…
Convolutional Deep Exponential Families
Chengkuan Hong, Christian R. Shelton
We describe convolutional deep exponential families (CDEFs) in this paper. CDEFs are built based on deep exponential families, deep probabilistic models that capture the hierarchic…