A VAE variant that uses polynomial powers of the input as separate encoder streams and an averaged KL loss is claimed to improve reconstruction and disentanglement, but the mathematical derivation and experiments do not support the claim as stated.
Recent advances in variational autoencoders with representation learning for biomedical informatics: A survey
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PH-VAE: A Polynomial Hierarchical Variational Autoencoder Towards Disentangled Representation Learning
A VAE variant that uses polynomial powers of the input as separate encoder streams and an averaged KL loss is claimed to improve reconstruction and disentanglement, but the mathematical derivation and experiments do not support the claim as stated.