10 papers
Loss-Shift Transfer via Bayes Quotients
Vasileios Sevetlidis
Transfer learning is usually studied as a consequence of distribution shift. This paper identifies an orthogonal failure mode in which the data distribution is fixed and the loss c…
Bayes-Sufficient Representations in Supervised Learning
Vasileios Sevetlidis
Representation learning is often described as preserving the information in an input that is relevant for prediction. This work asks what relevance means for a fixed supervised dec…
A Fiber Criterion for Representation Identifiability in Supervised Learning
Vasileios Sevetlidis
Supervised learning evaluates predictors through their input-output behavior. When a predictor is implemented as a composition , supervised evidence constrains the comp…
Towards complete digital twins in cultural heritage with ART3mis 3D artifacts annotator
Dimitrios Karamatskos, Vasileios Arampatzakis, Vasileios Sevetlidis +5
Archaeologists, as well as specialists and practitioners in cultural heritage, require applications with additional functions, such as the annotation and attachment of metadata to…
ART3mis: Ray-Based Textual Annotation on 3D Cultural Objects
Vasileios Arampatzakis, Vasileios Sevetlidis, Fotis Arnaoutoglou +7
Beyond simplistic 3D visualisations, archaeologists, as well as cultural heritage experts and practitioners, need applications with advanced functionalities. Such as the annotation…
Gauge-invariant representation holonomy
Vasileios Sevetlidis, George Pavlidis
Deep networks learn internal representations whose geometry--how features bend, rotate, and evolve--affects both generalization and robustness. Existing similarity measures such as…