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Active Learning for Discrete Latent Variable Models
Aditi Jha
, Zoe C. Ashwood
,
Jonathan W. Pillow
Princeton Neuroscience Institute
Princeton Language and Intelligence (PLI)
Research output
:
Contribution to journal
›
Letter
›
peer-review
4
Scopus citations
Overview
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Dive into the research topics of 'Active Learning for Discrete Latent Variable Models'. Together they form a unique fingerprint.
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Psychology
Regression Model
100%
Generalized Linear Model
100%
Hidden Markov Model
100%
Decision Making
50%
Neuroscience
50%
Gaussian Distribution
50%
Linear Regression
50%
Mathematics
Latent Variable Model
100%
Generalized Linear Model
50%
Regression Model
50%
Hidden Markov Model
50%
Mutual Information
25%
Approximates
25%
Gaussian Distribution
25%
Wide Variety
25%
Real-World Data
25%
Linear Regression
25%
Discrete State
25%
Scientific Discipline
25%
Fisher Information
25%
Social Sciences
Latent Variable
100%
Hidden Markov Model
40%
Decision Making
20%
Neuroscience
20%
Scientific Discipline
20%
Keyphrases
Information Input
20%
Mixture of Linear Regression
20%
Latent Variable Regression
20%
Computer Science
Fisher Information
20%
Variable Regression
20%