Abstract— There is widespread agreement that a higher level programming model for sensor networks is needed. A variety of models have been developed, but the community is far fro...
We extend the approach of model checking parameterized networks of processes by means of network invariants to the setting of real-time systems. We introduce timed transition stru...
In this paper, we investigate the impact of radio irregularity on the communication performance in wireless sensor networks. Radio irregularity is a common phenomenon which arises...
Gang Zhou, Tian He, Sudha Krishnamurthy, John A. S...
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...