The quantification of uncertainty is important for the adoption of machi...
We explore the utility of information contained within a dropout based
B...
The detection of malware is a critical task for the protection of comput...
We propose a cross-modality manifold alignment procedure that leverages
...
Non-pharmaceutical interventions (NPIs) have been crucial in curbing COV...
Deep neural networks (DNNs) are vulnerable to subtle adversarial
perturb...
We introduce the use of a Gated Recurrent Unit (GRU) for influenza predi...
Successful malware attacks on information technology systems can cause
m...
Recent work has developed Bayesian methods for the automatic statistical...
Significant work is being done to develop the math and tools necessary t...
Adversarial attacks against neural networks in a regression setting are ...