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Nature Communications|May 20, 2025
Modeling rapid language learning by distilling Bayesian priors into artificial neural networksR Thomas McCoy, Thomas L GriffithsCognitive Science|June 25, 2021
The Challenges of Large-Scale, Web-Based Language Datasets: Word Length and Predictability RevisitedStephan C Meylan, Thomas L GriffithsCognitive Science|May 14, 2011
Learning the form of causal relationships using hierarchical bayesian modelsChristopher G Lucas, Thomas L GriffithsThe Behavioral and Brain Sciences|September 23, 2024
Meta-learning as a bridge between neural networks and symbolic Bayesian modelsR Thomas McCoy, Thomas L GriffithsPsychological Review|November 14, 2013
A nonparametric Bayesian framework for constructing flexible feature representationsJoseph L Austerweil, Thomas L GriffithsCognition|May 9, 2006
From mere coincidences to meaningful discoveriesThomas L Griffiths, Joshua B TenenbaumMemory & Cognition|April 18, 2002
A multidimensional scaling approach to mental multiplicationThomas L Griffiths, Michael L KalishCognitive Psychology|September 23, 2011
A rational model of the effects of distributional information on feature learningJoseph L Austerweil, Thomas L GriffithsCognitive Science|July 9, 2024
Word Forms Reflect Trade-Offs Between Speaker Effort and Robust Listener RecognitionStephan C Meylan, Thomas L GriffithsCognitive Science|August 26, 2019
Sticking to the Evidence? A Behavioral and Computational Case Study of Micro-Theory Change in the Domain of MagnetismElizabeth Bonawitz, Tomer D Ullman, Sophie Bridgers, et al.Pageof 25