A deep learning approach to modeling spatial point patterns of locations of different tree species in a tropical rainforest
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Spatial point patterns of locations of trees in a rainforest are influenced by environmental conditions and many known and unknown ecological processes that are not directly observable. In this talk we propose a multilayer perceptrons model in order to relate the spatial patterns of trees to observed environmental variables and latent random fields, which accounts for all unobserved influential factors. We use the variational autoencoder approach to fit the proposed model and estimate (encode) the generative latent random fields.