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» Modeling affordances using Bayesian networks
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IEEEARES
2008
IEEE
15 years 4 months ago
Reliability Analysis using Graphical Duration Models
Reliability analysis has become an integral part of system design and operating. This is especially true for systems performing critical tasks such as mass transportation systems....
Roland Donat, Laurent Bouillaut, Patrice Aknin, Ph...
ICA
2010
Springer
14 years 11 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio
ESANN
2000
14 years 11 months ago
Confidence estimation methods for neural networks : a practical comparison
Feed-forward neural networks (Multi-Layered Perceptrons) are used widely in real-world regression or classification tasks. A reliable and practical measure of prediction "conf...
Georgios Papadopoulos, Peter J. Edwards, Alan F. M...
ICML
2005
IEEE
15 years 10 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell
IPSN
2004
Springer
15 years 3 months ago
A probabilistic approach to inference with limited information in sensor networks
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Rahul Biswas, Sebastian Thrun, Leonidas J. Guibas