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This work gives an in-depth derivation of the trainable evidence lower boundobtained from the marginal joint log-Likelihood with the goal of training aMulti-Modal Variational Autoencoder (M$^2$VAE).

M$^2$VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood