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ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
15 years 11 months ago
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Debprakash Patnaik, Srivatsan Laxman, Naren Ramakr...
AIME
2007
Springer
15 years 8 months ago
Using Temporal Context-Specific Independence Information in the Exploratory Analysis of Disease Processes
Abstract. Disease processes in patients are temporal in nature and involve uncertainty. It is necessary to gain insight into these processes when aiming at improving the diagnosis,...
Stefan Visscher, Peter J. F. Lucas, Ildikó ...
IPSN
2003
Springer
15 years 10 months ago
Maximum Mutual Information Principle for Dynamic Sensor Query Problems
In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
Emre Ertin, John W. Fisher, Lee C. Potter
CORR
2012
Springer
210views Education» more  CORR 2012»
14 years 12 days ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh
ICASSP
2011
IEEE
14 years 8 months ago
Uncover cooperative gene regulations by microRNAs and transcription factors in glioblastoma using a nonnegative hybrid factor mo
—Transcriptional regulation by transcription factors (TFs) and microRNAs controls when and how much RNA is created. Due to technical limitations, the protein level expressions of...
Jia Meng, Hung-I Harry Chen, Jianqiu Zhang, Yidong...