3 papers
cs.CV2026
A Geometric Unification of Generative AI with Manifold-Probabilistic Projection Models
Leah Bar, Liron Mor Yosef, Shai Zucker +3
Most models of generative AI for images assume that images are inherently low-dimensional objects embedded within a high-dimensional space. Additionally, it is often implicitly ass…
cs.LG2025
Flatness After All?
Neta Shoham, Liron Mor-Yosef, Haim Avron
Recent literature generalization in deep learning has examined the relationship between the curvature of the loss function at minima and generalization, mainly in the context of ov…
cs.LG2025
Unbiased Stochastic Optimization for Gaussian Processes on Finite Dimensional RKHS
Neta Shoham, Haim Avron
Current methods for stochastic hyperparameter learning in Gaussian Processes (GPs) rely on approximations, such as computing biased stochastic gradients or using inducing points in…