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Hidden variable theory

Known as: Hidden Variables, God does not play dice, Hidden-variable theories 
Historically, in physics, hidden variable theories were espoused by some physicists who argued that the state of a physical system, as formulated by… 
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Related topics

Related topics

38 relations
Action at a distanceBell stateBell test experimentsBell's theorem

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2013
2013
Zero resource spoken audio corpus analysis
Zero-resource speech processing involves the automatic analysis of a collection of speech data in a completely unsupervised… 
2013
2013
EM-GPA: Generalized Procrustes analysis with hidden variables for 3D shape modeling
Review
2009
Review
2009
on Aging Military Veterans lifespan Implications of Military Service
  • 2009
  • Corpus ID: 1097031
S continued was associated with significantly elevated PTSD symptom severity at the time of no PTSD diagnosis. No evidence was… 
2008
2008
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic… 
2008
2008
A generative retrieval model for structured documents
Structured documents contain elements defined by the author(s) and annotations assigned by other people or processes. Structured… 
2004
2004
Canonicalization of feature parameters for automatic speech recognition
Acoustic models (AMs) of an HMM-based classifier include various types of hidden variables such as gender type, speaking rate… 
2004
2004
Hidden failures in electric power systems
  • A. Phadke
  • Int. J. Crit. Infrastructures
  • 2004
  • Corpus ID: 32011837
Hidden failures in equipment are those failures which occur at random and that do not lead to any discernible change in the state… 
2002
2002
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many… 
2002
2002
A Nonlinear Observation Model for Removing Noise from Corrupted Speech Log Mel-Spectral Energies
In this paper we present a new statistical model, which describes the corruption to speech recognition Mel-frequency spectral… 
2001
2001
Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms
In this paper, a new method, called EM-EA, is put forward for learning Bayesian network structures from incomplete data. This… 
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