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Neural Gaussian Conditional Random Fields
2014We propose a Conditional Random Field (CRF) model for structured regression. By constraining the feature functions as quadratic functions of outputs, the model can be conveniently represented in a Gaussian canonical form. We improved the representational power of the resulting Gaussian CRF (GCRF) model by (1) introducing an adaptive feature function ...
Vladan Radosavljevic +2 more
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Kernel conditional random fields
Twenty-first international conference on Machine learning - ICML '04, 2004Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models is given which shows how kernel conditional random fields arise from risk minimization procedures defined using Mercer kernels on labeled graphs.
John D. Lafferty +2 more
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Temperature field in random conditions
International Journal of Heat and Mass Transfer, 1991Abstract A probabilistic finite-element approach for modelling the temperature field in structures is proposed. The theoretical formulation of the problem is described. It presents probabilistic distributions for temperature taking into account the random thermal properties of material.
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Fully Statistical, Wavelet-based conditional random field (FSWCRF) for SAR image segmentation
Expert Systems With Applications, 2021Mohammad Sadegh Helfroush +1 more
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Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields
Computers and Geotechnics, 2016M A Hicks
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Conditional random field reliability analysis of a cohesion-frictional slope
Computers and Geotechnics, 2017Shao-He Zhang
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