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cs.LG2025
Toward Architecture-Agnostic Local Control of Posterior Collapse in VAEs
Hyunsoo Song, Seungwhan Kim, Seungkyu Lee
Variational autoencoders (VAEs), one of the most widely used generative models, are known to suffer from posterior collapse, a phenomenon that reduces the diversity of generated sa…
cs.LG2024
Beta-Sigma VAE: Separating beta and decoder variance in Gaussian variational autoencoder
Seunghwan Kim, Seungkyu Lee
Variational autoencoder (VAE) is an established generative model but is notorious for its blurriness. In this work, we investigate the blurry output problem of VAE and resolve it,…