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.ME2025
Modeling Neural Switching via Drift-Diffusion Models
Nicholas Marco, Jennifer M. Groh, Surya T. Tokdar
Neural encoding is a field in neuroscience that focuses on characterizing how information from stimuli is encoded in the spiking activity of neurons. When more than one stimulus is…
stat.ME2024
Covariate Adjusted Functional Mixed Membership Models
Nicholas Marco, Damla Åentürk, Shafali Jeste +3
Mixed membership models are a flexible class of probabilistic data representations used for unsupervised and semi-supervised learning, allowing each observation to partially belong…