Targeting EEG/LFP Synchrony with Neural Nets

no code implementations • NeurIPS 2017 • Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, David E. Carlson

We consider the analysis of Electroencephalography (EEG) and Local Field Potential (LFP) datasets, which are “big” in terms of the size of recorded data but rarely have sufficient labels required to train complex models (e. g., conventional deep learning methods).

EEG

Extracting Relationships by Multi-Domain Matching

1 code implementation • NeurIPS 2018 • Yitong Li, Michael Murias, Geraldine Dawson, David E. Carlson

This methodology builds on existing distribution-matching approaches by assuming that source domains are varied and outcomes multi-factorial.

Domain Adaptation Time Series +2

On Target Shift in Adversarial Domain Adaptation

no code implementations • 15 Mar 2019 • Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, David E. Carlson

In this work, we propose a method called Domain Adversarial nets for Target Shift (DATS) to address label shift while learning a domain invariant representation.

Domain Adaptation

Adversarial Factor Models for the Generation of Improved Autism Diagnostic Biomarkers

no code implementations • 24 Sep 2021 • William E. Carson IV, Dmitry Isaev, Samatha Major, Guillermo Sapiro, Geraldine Dawson, David Carlson

Second, we show this same model can be used to learn a disentangled representation of multimodal biomarkers that results in an increase in predictive performance.