Author
Georgia Institute of Technology
Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.
4 papers
Recent·Most cited
Charles A. Ellis, Mohammad S.E. Sendi, Rongen Zhang…·Vince D. Calhoun
This study develops novel methods to assess modality importance in multimodal electrophysiology classifiers, finding EEG is globally most important for sleep stages except stage 1, with subject-level differences influenced by sex, medication, and age.
Charles A. Ellis, Rongen Zhang, Darwin A. Carbajal…·May Dongmei Wang
This study classifies sleep stages using multimodal electrophysiology data and introduces an ablation method to assess modality importance, finding EEG is most important for most stages and EOG for REM and nonREM.
Charles A. Ellis, Darwin A. Carbajal, Rongen Zhang…·May Dongmei Wang
This paper introduces a local ablation method to explain multimodal classifiers, showing EEG's importance in sleep staging and identifying demographic effects on classification.
Charles A. Ellis, Darwin A. Carbajal, Rongen Zhang…·May Dongmei Wang
The paper introduces a gradient-based explainability method for multimodal electrophysiology classifiers, showing EEG's dominance in sleep stage classification.