NIPS Proceedingsβ

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)