Search Results for author:
Found 5 papers, 0 papers with code
A hybrid convolutional neural network/active contour approach to segmenting dead trees in aerial imagery
This improved performance is essential to meet emerging challenges caused by climate change (and other man-made perturbations to the systems), particularly to monitor and estimate carbon stock decay rates, monitor forest health and biodiversity, and the overall effects of dead wood on and from climate change.
GP-select: Accelerating EM using adaptive subspace preselection
We propose a nonparametric procedure to achieve fast inference in generative graphical models when the number of latent states is very large.
A Truncated EM Approach for Spike-and-Slab Sparse Coding
We investigate two approaches to optimize the parameters of spike-and-slab sparse coding: a novel truncated EM approach and, for comparison, an approach based on standard factored variational distributions.
Select and Sample - A Model of Efficient Neural Inference and Learning
We demonstrate the effectiveness and efficiency of this approach on a sparse coding model.
Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity
Resting state activity is brain activation that arises in the absence of any task, and is usually measured in awake subjects during prolonged fMRI scanning sessions where the only instruction given is to close the eyes and do nothing.
