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» Inferring Hidden Causal Structure
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IBERAMIA
2004
Springer
14 years 4 months ago
Statistical Inference in Mapping and Localization for Mobile Robots
In this paper we tackle the problem of providing a mobile robot with the ability to build a map of its environment using data gathered during navigation. The data correspond to the...
Anita Araneda, Alvaro Soto
CVPR
2012
IEEE
12 years 1 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller
BMCBI
2010
229views more  BMCBI 2010»
13 years 11 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
CVPR
1999
IEEE
15 years 28 days ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
FORMATS
2005
Springer
14 years 4 months ago
Time Supervision of Concurrent Systems Using Symbolic Unfoldings of Time Petri Nets
Monitoring real-time concurrent systems is a challenging task. In this paper we formulate (model-based) supervision by means of hidden state history reconstruction, from event (e.g...
Thomas Chatain, Claude Jard