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Learning in Integer Latent Variable Models with Nested Automatic Differentiation
We develop nested automatic differentiation (AD) algorithms for exact inference and learning in integer latent variable models.
Probabilistic Inference with Generating Functions for Poisson Latent Variable Models
We present the first exact inference algorithms for a class of models with latent count variables by developing a novel representation of countably infinite factors as probability generating functions, and then performing variable elimination with generating functions.
Exact Inference for Integer Latent-Variable Models
This substantially generalizes the class of models for which efficient, exact inference algorithms are available.
Species Distribution Modeling for Machine Learning Practitioners: A Review
How many species live there?
