3 papers
stat.ME2026
Mixed Membership Models for Multilevel Functional Data
Donatello Telesca, Nicholas Marco, Emma Landry
Mixed membership models extend classical clustering by substituting the notion of uncertain membership with the notion of mixed membership. In particular, these models allow each o…
stat.AP2026
Transporting Predictions via Double Machine Learning: Predicting Partially Unobserved Students' Outcomes
Falco J. Bargagli-Stoffi, Emma Landry, Kevin P. Josey +3
Educational policymakers often lack data on student outcomes where standardized tests were not administered. Machine learning can predict unobserved outcomes in target populations…
stat.ME2024
Modeling EEG Spectral Features through Warped Functional Mixed Membership Models
Emma Landry, Damla Senturk, Shafali Jeste +3
A common concern in the field of functional data analysis is the challenge of temporal misalignment, which is typically addressed using curve registration methods. Currently, most…