Recent progress in EDA tools allows IC designs to be accurately verified with consequent improvements in yield and performance through reduced guard bands. This paper will present...
In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to cre...
Anders Brun, Hans Knutsson, Hae-Jeong Park, Martha...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Spacecraft increasingly employ onboard data analysis to inform further data collection and prioritization decisions. However, many spacecraft operate in high-radiation environment...
This paper introduces a new problem for which machine-learning tools may make an impact. The problem considered is termed "compressive sensing", in which a real signal o...