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» Probabilistic Neural Network Models for Sequential Data
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CVIU
2006
158views more  CVIU 2006»
13 years 8 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu
UAI
1997
13 years 9 months ago
Sequential Update of Bayesian Network Structure
There is an obvious need for improving the performance and accuracy of a Bayesian network as new data is observed. Because of errors in model construction and changes in the dynam...
Nir Friedman, Moisés Goldszmidt
IJCNN
2008
IEEE
14 years 2 months ago
A comparison of bayesian and conditional density models in probabilistic ozone forecasting
— Probabilistic models were developed to provide predictive distributions of daily maximum surface level ozone concentrations. Five forecast models were compared at two stations ...
Song Cai, William W. Hsieh, Alex J. Cannon
NPL
2006
137views more  NPL 2006»
13 years 8 months ago
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Chih-Ming Chen, Yung-Feng Lu, Chin-Ming Hong
ICMLA
2009
13 years 6 months ago
Learning Deep Neural Networks for High Dimensional Output Problems
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Benjamin Labbé, Romain Hérault, Cl&e...