# Large-Scale Cox Process Inference using Variational Fourier Features

@article{John2018LargeScaleCP, title={Large-Scale Cox Process Inference using Variational Fourier Features}, author={S. T. John and James Hensman}, journal={ArXiv}, year={2018}, volume={abs/1804.01016} }

Gaussian process modulated Poisson processes provide a flexible framework for modelling spatiotemporal point patterns. So far this had been restricted to one dimension, binning to a pre-determined grid, or small data sets of up to a few thousand data points. Here we introduce Cox process inference based on Fourier features. This sparse representation induces global rather than local constraints on the function space and is computationally efficient. This allows us to formulate a grid-free…

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