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Pro-t-VAE: Closed-Form Student's t Mixtures for Robust Prototype Discovery
We present a robust deep generative framework for unsupervised image prototype discovery, built on a heavy-tailed Student's t mixture prior, that bridges statistical robustness and mathematical tractability. Existing generative approaches typically rely on noise-prone Gaussian priors or computationa
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