Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Flow visualization has been a very active subfield of scientific visualization in recent years. From the resulting large variety of methods this paper discusses partition-based te...
Background: A protein structural class (PSC) belongs to the most basic but important classification in protein structures. The prediction technique of protein structural class has...
Given the set [n] = {1, . . . , n} for positive integer n, combinatorial properties of Clifford algebras are exploited to count partitions and nonoverlapping partitions of [n]. Th...
We give a self-contained and streamlined version of the classification of the provably computable functions of PA. The emphasis is put on illuminating as good as seems possible th...