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.ME2026
Bayesian Transfer Learning for High-Dimensional Linear Regression via Adaptive Shrinkage
Parsa Jamshidian, Donatello Telesca
We introduce BLAST, Bayesian Linear regression with Adaptive Shrinkage for Transfer, a Bayesian multi-source transfer learning framework for high-dimensional linear regression. The…
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…