CoDE-VAE computes the shared latent code of multiple data views by Bayesian combination of correlated per-view estimates, improving coherence/quality trade-offs and log-likelihood bounds.
Models are trained on single A100 GPUs with AMD EPYC Milan processors with 24 cores
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Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
CoDE-VAE computes the shared latent code of multiple data views by Bayesian combination of correlated per-view estimates, improving coherence/quality trade-offs and log-likelihood bounds.