Autoencoding probabilistic circuits train a single probabilistic circuit to jointly model data and explicit embedding variables, enabling end-to-end autoencoding with neural decoders and robust encoding under missing data.
This comparison highlights the flexibility of APCs compared to the prior autoencoding scheme introduced in Vergari et al
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Tractable Representation Learning with Probabilistic Circuits
Autoencoding probabilistic circuits train a single probabilistic circuit to jointly model data and explicit embedding variables, enabling end-to-end autoencoding with neural decoders and robust encoding under missing data.