In a first stage, training each of a plurality of first variational auto encoders, VAEs, each comprising: a respective first encoder arranged to encode a respective subset of one or more features of a feature space into a respective first latent representation, and a respective first decoder arranged to decode from the respective latent representation back to a decoded version of the respective subset of the feature space, wherein different subsets comprise features of different types of data. In a second stage following the first stage, training a second VAE comprising: a second encoder arranged to encode a plurality of inputs into a second latent representation, and a second decoder arranged to decode the second latent representation into decoded versions of the first latent representations, wherein each of the plurality of inputs comprises a combination of a different respective one of feature subsets with the respective first latent representation.
Variational auto encoder for mixed data types
2020-06-24
Patent
Electronic Resource
English
Causal Intervention Framework for Variational Auto Encoder Mechanistic Interpretability
ArXiv | 2025
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