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fredshone / citychef Public

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pops needed for ABMs, made from samples

curse of dims

smoothing aka not sampling

zero sampling

VAE compared to trad models: Gibbs and Bayesian net

VAEs learn underlying joint probabilities in high dimensional data

VAE (specifically Dl) can be extended to better accomodate spatial, graph and sequential popukation characteristics (ie locations, networks and activity plans)

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