Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families

arXiv:2402.09608v1 Announce Type: new
Abstract: We introduce squared neural Poisson point processes (SNEPPPs) by parameterising the intensity function by the squared norm of a two layer neural network. When the hidden layer is fixed and the second layer has a single neuron, our approach resembles previous uses of squared Gaussian process or kernel methods, but allowing the hidden layer to be learnt allows for additional flexibility. In many cases of interest, the integrated intensity function admits a closed form and …

arxiv cs.lg families processes stat.ml type via