3 papers
stat.ML2025
End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
Yidong Zhou, Su I Iao, Hans-Georg Müller
Many modern applications involve predicting structured, non-Euclidean outputs such as probability distributions, networks, and symmetric positive-definite matrices. These outputs a…
stat.ME2025
Inference for Dispersion and Curvature of Random Objects
Wookyeong Song, Hans-Georg Müller
There are many open questions pertaining to the statistical analysis of random objects, which are increasingly encountered. A major challenge is the absence of linear operations in…
stat.ME2024
Deep Fréchet Regression
Su I Iao, Yidong Zhou, Hans-Georg Müller
Advancements in modern science have led to the increasing availability of non-Euclidean data in metric spaces. This paper addresses the challenge of modeling relationships between…