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» Two Algorithms for Inducing Causal Models from Data
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NIPS
2007
13 years 10 months ago
Comparing Bayesian models for multisensory cue combination without mandatory integration
Bayesian models of multisensory perception traditionally address the problem of estimating an underlying variable that is assumed to be the cause of the two sensory signals. The b...
Ulrik Beierholm, Konrad P. Körding, Ladan Sha...
ISBI
2006
IEEE
14 years 9 months ago
Two probabilistic algorithms for MEG/EEG source reconstruction
We have developed two algorithms for source imaging from MEG/EEG data. Contribution to sensor data from a source at a particular voxel is expressed as the product of a known lead ...
Johanna M. Zumer, Hagai Attias, Kensuke Sekihara, ...
UMUAI
2008
110views more  UMUAI 2008»
13 years 8 months ago
Modeling self-efficacy in intelligent tutoring systems: An inductive approach
Abstract. Self-efficacy is an individual's belief about her ability to perform well in a given situation. Because selfefficacious students are effective learners, endowing int...
Scott W. McQuiggan, Bradford W. Mott, James C. Les...
ICCV
2005
IEEE
14 years 2 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
NIPS
2004
13 years 9 months ago
Instance-Specific Bayesian Model Averaging for Classification
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
Shyam Visweswaran, Gregory F. Cooper