• Publications
  • Influence
Probabilistic Topic Models
  • 892
  • 91
The Large-Scale Structure of Semantic Networks
  • 65
  • 11
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A method for efficiently sampling from distributions with correlated dimensions.
Bayesian estimation has played a pivotal role in the understanding of individual differences. However, for many models in psychology, Bayesian estimation of model parameters can be difficult. OneExpand
  • 154
  • 6
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Accumulative prediction error and the selection of time series models
TLDR
We explore the rationale for using accumulative one-step-ahead prediction error (APE) as a data-driven method for model selection. Expand
  • 96
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Computational Statistics with Matlab
  • 18
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Morphing techniques for manipulating face images
  • M. Steyvers
  • Computer Science, Medicine
  • Behavior research methods, instruments…
  • 1 June 1999
TLDR
This paper describes morphing techniques to manipulate two-dimensional human face images and three-dimensional models of the human head. Expand
  • 64
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Scalable Parallel Topic Models
TLDR
We present a parallel algorithm for the topic model that has linear speedup and high parallel efficiency for shared-memory symmetric multiprocessors. Expand
  • 23
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Joint Models of Neural and Behavioral Data
TLDR
This book presents a flexible Bayesian framework for combining neural and cognitive models that allows the neural data to influence the parameters of the cognitive model and allows behavioral data to constrain the neural model. Expand
  • 11
Hierarchical Bayesian Analyses for Modeling BOLD Time Series Data
TLDR
We use the convolution technique as a basis for describing neural time series data and develop five models to describe how subject-, condition-, and brain-area-specific effects interact. Expand
  • 4
  • PDF