5 citations · 7 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 2 cited
Using Convolutional Variational Autoencoders to Predict Post-Trauma Health Outcomes from Actigraphy Data
Ayse S. Cakmak, Nina Thigpen, Garrett Honke +9
Depression and post-traumatic stress disorder (PTSD) are psychiatric conditions commonly associated with experiencing a traumatic event. Estimating mental health status through non…
cs.LG2020★ 5 cited
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Garrett Honke, Irina Higgins, Nina Thigpen +6
Despite extensive standardization, diagnostic interviews for mental health disorders encompass substantial subjective judgment. Previous studies have demonstrated that EEG-based ne…
cs.LG2020
Unsupervised Foveal Vision Neural Networks with Top-Down Attention
Ryan Burt, Nina N. Thigpen, Andreas Keil +1
Deep learning architectures are an extremely powerful tool for recognizing and classifying images. However, they require supervised learning and normally work on vectors the size o…