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NIPS
2008
9 years 1 months ago
Using Bayesian Dynamical Systems for Motion Template Libraries
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 ...
Silvia Chiappa, Jens Kober, Jan Peters
EMNLP
2008
9 years 1 months ago
A Generative Model for Parsing Natural Language to Meaning Representations
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...
AMDO
2008
Springer
9 years 2 months ago
A Generative Model for Motion Synthesis and Blending Using Probability Density Estimation
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...
Dumebi Okwechime, Richard Bowden
CVPR
2004
IEEE
9 years 3 months ago
Modeling Complex Motion by Tracking and Editing Hidden Markov Graphs
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...
Yizhou Wang, Song Chun Zhu
AMDO
2006
Springer
9 years 3 months ago
Carrying Object Detection Using Pose Preserving Dynamic Shape Models
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...
Chan-Su Lee, Ahmed M. Elgammal
SIGGRAPH
1999
ACM
9 years 4 months ago
Creating Generative Models from Range Images
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...
Ravi Ramamoorthi, James Arvo
SCVMA
2004
Springer
9 years 5 months ago
A Generative Model of Dense Optical Flow in Layers
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...
Anitha Kannan, Brendan J. Frey, Nebojsa Jojic
ECML
2004
Springer
9 years 5 months ago
Fisher Kernels for Logical Sequences
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...
Kristian Kersting, Thomas Gärtner
RECOMB
2005
Springer
9 years 5 months ago
Probabilistic in Silico Prediction of Protein-Peptide Interactions
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....
INEX
2005
Springer
9 years 5 months ago
Parameter Estimation for a Simple Hierarchical Generative Model for XML Retrieval
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...
Paul Ogilvie, Jamie Callan
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