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SAC
2008
ACM
13 years 7 months ago
Bayesian inference for a discretely observed stochastic kinetic model
The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observ...
Richard J. Boys, Darren J. Wilkinson, Thomas B. L....
NAACL
2010
13 years 6 months ago
Bayesian Inference for Finite-State Transducers
We describe a Bayesian inference algorithm that can be used to train any cascade of weighted finite-state transducers on end-toend data. We also investigate the problem of automat...
David Chiang, Jonathan Graehl, Kevin Knight, Adam ...
ACCV
2010
Springer
13 years 3 months ago
Network Connectivity via Inference over Curvature-Regularizing Line Graphs
Abstract. Diffusion Tensor Imaging (DTI) provides estimates of local directional information regarding paths of white matter tracts in the human brain. An important problem in DTI ...
Maxwell D. Collins, Vikas Singh, Andrew L. Alexand...
IJON
2010
109views more  IJON 2010»
13 years 3 months ago
Variational inference for Student-t MLP models
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
Hang T. Nguyen, Ian T. Nabney
ICCV
1999
IEEE
14 years 10 months ago
Prediction Error as a Quality Metric for Motion and Stereo
This paper presents a new methodology for evaluating the quality of motion estimation and stereo correspondence algorithms. Motivated by applications such as novel view generation...
Richard Szeliski