38 citations · 70 across the 3 of their papers we have counts for
3 papers
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
Bahareh Tolooshams, Andrew H. Song, Simona Temereanca +1
We introduce a class of auto-encoder neural networks tailored to data from the natural exponential family (e.g., count data). The architectures are inspired by the problem of learn…
A Spatiotemporal Dynamic Solution to the MEG Inverse Problem: An Empirical Bayes Approach
Camilo Lamus, Matti S. Hämäläinen, Simona Temereanca +2
MEG/EEG are non-invasive imaging techniques that record brain activity with high temporal resolution. However, estimation of brain source currents from surface recordings requires…
State-space solutions to the dynamic magnetoencephalography inverse problem using high performance computing
Christopher J. Long, Patrick L. Purdon, Simona Temereanca +3
Determining the magnitude and location of neural sources within the brain that are responsible for generating magnetoencephalography (MEG) signals measured on the surface of the he…