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» Approximate Learning of Dynamic Models
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IDA
2003
Springer
15 years 7 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
ISBI
2004
IEEE
16 years 3 months ago
Covariance of Kinetic Parameter Estimators Based on Time Activity Curve Reconstructions: Preliminary Study on 1D Dynamic Imaging
We provide approximate expressions for the covariance matrix of kinetic parameter estimators based on time activity curve (TAC) reconstructions when TACs are modeled as a linear c...
Sangtae Ahn, Jeffrey A. Fessler, Thomas E. Nichols...
ECML
2006
Springer
15 years 6 months ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...
AMC
2006
77views more  AMC 2006»
15 years 2 months ago
A reduced three-dimensional dynamic structural model for structural health assessment
Dynamic models of elastic structures are derived using approximations of linear three dimensional elasticity. A model for the three dimensional motion of a nonsymmetric structure ...
Luther White
DSMML
2004
Springer
15 years 7 months ago
Can Gaussian Process Regression Be Made Robust Against Model Mismatch?
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...
Peter Sollich