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» Probabilistic Neural Network Models for Sequential Data
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NN
2006
Springer
121views Neural Networks» more  NN 2006»
13 years 8 months ago
Mirror neurons and imitation: A computationally guided review
Neurophysiology reveals the properties of individual mirror neurons in the macaque while brain imaging reveals the presence of `mirror systems' (not individual neurons) in th...
Erhan Oztop, Mitsuo Kawato, Michael A. Arbib
IDEAL
2005
Springer
14 years 1 months ago
Predictive Vaccinology: Optimisation of Predictions Using Support Vector Machine Classifiers
Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidd...
Ivana Bozic, Guanglan Zhang, Vladimir Brusic
CC
2010
Springer
190views System Software» more  CC 2010»
14 years 2 months ago
Is Reuse Distance Applicable to Data Locality Analysis on Chip Multiprocessors?
On Chip Multiprocessors (CMP), it is common that multiple cores share certain levels of cache. The sharing increases the contention in cache and memory-to-chip bandwidth, further h...
Yunlian Jiang, Eddy Z. Zhang, Kai Tian, Xipeng She...
MICCAI
2006
Springer
14 years 9 months ago
Logarithm Odds Maps for Shape Representation
The concept of the Logarithm of the Odds (LogOdds) is frequently used in areas such as artificial neural networks, economics, and biology. Here, we utilize LogOdds for a shape repr...
Kilian M. Pohl, John W. Fisher III, Martha Elizabe...
NIPS
2003
13 years 9 months ago
Nonstationary Covariance Functions for Gaussian Process Regression
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
Christopher J. Paciorek, Mark J. Schervish