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» Introduction to Causal Inference
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JBI
2002
14 years 9 months ago
Revising regulatory networks: from expression data to linear causal models
Discovering the complex regulatory networks that govern mRNA expression is an important but difficult problem. Many current approaches use only expression data from microarrays to...
Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pa...
NAR
2010
123views more  NAR 2010»
14 years 4 months ago
Discovering causal signaling pathways through gene-expression patterns
High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant members...
Jignesh R. Parikh, Bertram Klinger, Yu Xia, Jarrod...

Publication
253views
14 years 7 months ago
Multisensory Oddity Detection as Bayesian Inference
A key goal for the perceptual system is to optimally combine information from all the senses that may be available in order to develop the most accurate and unified picture possi...
Timothy Hospedales and Sethu Vijayakumar
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
15 years 10 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
VLDB
1998
ACM
147views Database» more  VLDB 1998»
15 years 1 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...