Motor primitives or motion templates have become an important concept for both modeling human motor control as well as generating robot behaviors using imitation learning. Recent ...
In this paper, we present an algorithm for learning a generative model of natural language sentences together with their formal meaning representations with hierarchical structure...
Wei Lu, Hwee Tou Ng, Wee Sun Lee, Luke S. Zettlemo...
The main focus of this paper is to present a method of reusing motion captured data by learning a generative model of motion. The model allows synthesis and blending of cyclic moti...
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
In this paper, we introduce a framework for carrying object detection in different people from different views using pose preserving dynamic shape models. We model dynamic shape de...
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Abstract. Peptide recognition modules (PRMs) are specialised compact protein domains that mediate many important protein-protein interactions. They are responsible for the assembly...
Wolfgang P. Lehrach, Dirk Husmeier, Christopher K....
Abstract. This paper explores the possibility of using a modified Expectation-Maximization algorithm to estimate parameters for a simple hierarchical generative model for XML retr...