NIPS Proceedings
^{β}
Books
Thomas L. Griffiths
30 Papers
Human memory search as a random walk in a semantic network
(2012)
An ideal observer model for identifying the reference frame of objects
(2011)
A rational model of causal inference with continuous causes
(2011)
Testing a Bayesian Measure of Representativeness Using a Large Image Database
(2011)
Learning invariant features using the Transformed Indian Buffet Process
(2010)
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning
(2009)
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling
(2009)
Nonparametric Latent Feature Models for Link Prediction
(2009)
Analyzing human feature learning as nonparametric Bayesian inference
(2008)
A rational model of preference learning and choice prediction by children
(2008)
How memory biases affect information transmission: A rational analysis of serial reproduction
(2008)
Modeling human function learning with Gaussian processes
(2008)
Modeling the effects of memory on human online sentence processing with particle filters
(2008)
A Probabilistic Approach to Language Change
(2007)
Markov Chain Monte Carlo with People
(2007)
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models
(2006)
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments
(2006)
Particle Filtering for Nonparametric Bayesian Matrix Factorization
(2006)
Infinite latent feature models and the Indian buffet process
(2005)
Interpolating between types and tokens by estimating power-law generators
(2005)
Integrating Topics and Syntax
(2004)
Parametric Embedding for Class Visualization
(2004)
From Algorithmic to Subjective Randomness
(2003)
Hierarchical Topic Models and the Nested Chinese Restaurant Process
(2003)
Semi-Supervised Learning with Trees
(2003)
Dynamical Causal Learning
(2002)
Prediction and Semantic Association
(2002)
Theory-Based Causal Inference
(2002)
Using Vocabulary Knowledge in Bayesian Multinomial Estimation
(2001)
Structure Learning in Human Causal Induction
(2000)