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Kaede Shiohara

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#machine learning Preprint Oct 2026

Empirical Variational Autoencoder

We present Empirical Variational Autoencoder, a general generative framework for continuous-valued (i.e., non-vector-quantized) sequences. EVA is based on the evidence lower bound of the Variational Autoencoder (VAE) but learns autoregressive latent priors empirically from training data, which can be implemented only b...

Kaede Shiohara · 0 citations