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NIPS
2007
15 years 7 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
EVOW
2008
Springer
15 years 8 months ago
Detection of Quantitative Trait Associated Genes Using Cluster Analysis
Abstract. Many efforts have been involved in association study of quantitative phenotypes and expressed genes. The key issue is how to efficiently identify phenotype-associated gen...
Zhenyu Jia, Sha Tang, Dan Mercola, Shizhong Xu
ICIP
2003
IEEE
16 years 7 months ago
A Bayesian approach to inclusion and performance analysis of using extra information in bioelectric inverse problems
Due to attenuation and spatial smoothing that occurs in the conducting media, the bioelectric inverse problem of estimating sources from remote measurements is ill-posed and solut...
Yesim Serinagaoglu, Dana H. Brooks, Robert S. MacL...
ICASSP
2011
IEEE
14 years 10 months ago
Unsupervised determination of efficient Korean LVCSR units using a Bayesian Dirichlet process model
Korean is an agglutinative language that does not have explicit word boundaries. It is also a highly inflective language that exhibits severe coarticulation effects. These charac...
Sakriani Sakti, Andrew M. Finch, Ryosuke Isotani, ...
FMOODS
2003
15 years 7 months ago
A Rewriting Based Model for Probabilistic Distributed Object Systems
Concurrent and distributed systems have traditionally been modelled using nondeterministic transitions over configurations. The minism provides an abstraction over scheduling, net...
Nirman Kumar, Koushik Sen, José Meseguer, G...