We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
In the demonstration, we will present the concepts and an implementation of an inductive database ? as proposed by Imielinski and Mannila ? in the relational model. The goal is to...
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such...
Abstract- We introduce metrics on sensorimotor experience at various temporal scales based on informationtheory. Sensorimotor variables through which the experience of an agent fl...