We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are incorporated by adding ad-hoc rules to a working grammar; subseque...
Sequence mining is an important data mining task. In order to retrieve interesting sequences from a large database, a minimum support threshold is needed to be specified. Unfortun...
We present an adaptive out-of-core technique for rendering massive scalar volumes employing single pass GPU raycasting. The method is based on the decomposition of a volumetric dat...
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
— DNA sequence basecalling is commonly regarded as a solved problem, despite significant error rates being reflected in inaccuracies in databases and genome annotations. This has...