Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
The Decision Tree Learning Algorithms (DTLAs) are getting keen attention from the natural language processing research comlnunity, and there have been a series of attempts to appl...
Loop closure in proteins requires computing the values of the inverse kinematics (IK) map for a backbone fragment with 2n 6 torsional degrees of freedom (dofs). It occurs in a va...
R. James Milgram, Guanfeng Liu, Jean-Claude Latomb...
Abstract. We present the application of Cascade Correlation for structures to QSPR (quantitative structureproperty relationships) and QSAR (quantitative structure-activity relation...
Anna Maria Bianucci, Alessio Micheli, Alessandro S...
Many traditional methods for shape classification involve
establishing point correspondences between shapes to
produce matching scores, which are in turn used as similarity
meas...