This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Shrinking feature sizes and process variations are of increasing concern in modern technology. It is urgent that we develop statistical interconnect timing models which are harmon...
We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by ...
Jason A. Palmer, Kenneth Kreutz-Delgado, Bhaskar D...
Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ale...