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ESWA
2006
103views more  ESWA 2006»
13 years 8 months ago
Model gene network by semi-fixed Bayesian network
Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, le...
Tie-Fei Liu, Wing-Kin Sung, Ankush Mittal
TASLP
2002
109views more  TASLP 2002»
13 years 8 months ago
Particle methods for Bayesian modeling and enhancement of speech signals
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, S...
FPGA
2010
ACM
232views FPGA» more  FPGA 2010»
13 years 8 months ago
High-throughput bayesian computing machine with reconfigurable hardware
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Mingjie Lin, Ilia Lebedev, John Wawrzynek
ICRA
2007
IEEE
199views Robotics» more  ICRA 2007»
14 years 3 months ago
Automatic Outlier Detection: A Bayesian Approach
— In order to achieve reliable autonomous control in advanced robotic systems like entertainment robots, assistive robots, humanoid robots and autonomous vehicles, sensory data n...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
14 years 13 days ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang