We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Abstract—The highly stochastic nature of wireless environments makes it desirable to monitor link loss rates in wireless sensor networks. In this paper, we study the loss inferen...
Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
This paper presents a proto-type autonomous signal processing system on a chip. The system is architected such that high performance digital signal processing occurs in the FPGAâ€...
Determining the relationship between structure (i.e. morphology) and function is a fundamental problem in brain research. In this paper we present a new framework based on Bayesia...
Hanchuan Peng, Edward Herskovits, Christos Davatzi...