AI RESEARCH
Improving Conditional VAE with Non-Volume Preserving transformations
arXiv CS.LG
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ArXi:2511.08946v4 Announce Type: replace Variational Autoencoders and Generative Adversarial Networks remained the state-of-the-art (SOTA) generative models until 2022. Now they are superseded by diffusion-based models. Efforts to improve traditional models have stagnated as a result. In old-school fashion, we explore image generation with conditional Variational Autoencoders (CVAE) to incorporate desired attributes within the images.