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cs.LG2026
A Theory of Speciation in Generative Diffusion Models on Compact Riemannian Manifolds
Alessio Marta, Paola Causin
Speciation in generative diffusion models denotes the emergence of distinct stable branches during denoising, through which initially undifferentiated trajectories progressively co…
cs.LG2025
Estimating Dataset Dimension via Singular Metrics under the Manifold Hypothesis: Application to Inverse Problems
Paola Causin, Alessio Marta
High-dimensional datasets often exhibit low-dimensional geometric structures, as suggested by the manifold hypothesis, which implies that data lie on a smooth manifold embedded in…
cs.LG2024
Unveiling Transformer Perception by Exploring Input Manifolds
Alessandro Benfenati, Alfio Ferrara, Alessio Marta +2
This paper introduces a general method for the exploration of equivalence classes in the input space of Transformer models. The proposed approach is based on sound mathematical the…