Abstract. Filter networks, i.e. decomposition of a filter set into a layered structure of sparse subfilters has been proven successful for e.g. efficient convolution using finit...
Background: The post-genomic era is characterised by a torrent of biological information flooding the public databases. As a direct consequence, similarity searches starting with ...
Anne Friedrich, Raymond Ripp, Nicolas Garnier, Emm...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
With the continued growth of three dimensional structural information databases comes a corresponding increase in interest in this data for the study of new sequences and an ever-...
Paulo Lai, Warren Kaplan, W. Bret Church, Raymond ...
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...