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cs.LG2025
Multivariate Variational Autoencoder
Mehmet Can Yavuz
Learning latent representations that are simultaneously expressive, geometrically well-structured, and reliably calibrated remains a central challenge for Variational Autoencoders…
cs.LG2025
Evaluating the Efficiency of Latent Spaces via the Coupling-Matrix
Mehmet Can Yavuz, Berrin Yanikoglu
A central challenge in representation learning is constructing latent embeddings that are both expressive and efficient. In practice, deep networks often produce redundant latent s…
cs.LG2025
Variational Self-Supervised Learning
Mehmet Can Yavuz, Berrin Yanikoglu
We present Variational Self-Supervised Learning (VSSL), a novel framework that combines variational inference with self-supervised learning to enable efficient, decoder-free repres…