1 citations · 1 across the 7 of their papers we have counts for
7 papers
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…
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…
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…
Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting Operation
Mehmet Can Yavuz, Yang Yang
In biomedical imaging analysis, the dichotomy between 2D and 3D data presents a significant challenge. While 3D volumes offer superior real-world applicability, they are less avail…
Policy Gradient-Driven Noise Mask
Mehmet Can Yavuz, Yang Yang
Deep learning classifiers face significant challenges when dealing with heterogeneous multi-modal and multi-organ biomedical datasets. The low-level feature distinguishability limi…
Variational Self-Supervised Contrastive Learning Using Beta Divergence
Mehmet Can Yavuz, Berrin Yanikoglu
Learning a discriminative semantic space using unlabelled and noisy data remains unaddressed in a multi-label setting. We present a contrastive self-supervised learning method whic…