Joud A.

Artificial Intelligence Specialization · Cohort 2026

OLVAE:One Loss Variational AutoEncoder

This research paper investigates a generative autoencoder that enables both image reconstruction and generation without relying on the KL divergence used in standard Variational Autoencoders (VAEs). The proposed approach combines SVD-based latent regularization with multiplicative Gaussian noise to structure the latent space while maintaining effective reconstruction and generation capabilities.

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