Thomas L. Griffiths
Affiliations: | University of California, Berkeley, Berkeley, CA |
Area:
computationWebsite:
http://cocosci.berkeley.edu/tom/Google:
"Thomas Griffiths"Mean distance: 14.04 (cluster 23) | S | N | B | C | P |
Parents
Sign in to add mentor| Joshua Tenenbaum | grad student | 2005 | Stanford | |
| (Causes, coincidences, and theories.) | ||||
Children
Sign in to add trainee| Jay B. Martin | research assistant | 2007-2010 | UC Berkeley |
| Christopher Ramsay Holdgraf | research assistant | 2010-2011 | UC Berkeley |
| Tiffany Jean Hwu | research assistant | 2012-2014 | UC Berkeley |
| Paul M. Krueger | grad student | ||
| Joshua Abbott | grad student | 2010- | UC Berkeley |
| Michael Pacer | grad student | 2010- | UC Berkeley |
| Jessica B. Hamrick | grad student | 2012- | UC Berkeley |
| Rachit Dubey | grad student | 2016- | |
| Sreejan Kumar | grad student | 2019- | |
| Adam N. Sanborn | grad student | 2005-2006 | Brown |
| Lei Shi | grad student | 2009 | UC Berkeley |
| Christopher G. Lucas | grad student | 2006-2010 | UC Berkeley |
| Kevin Robert Canini | grad student | 2011 | UC Berkeley |
| Joseph L. Austerweil | grad student | 2007-2012 | UC Berkeley |
| Joseph Jay Williams | grad student | 2007-2012 | UC Berkeley |
| Anna Noonan Rafferty | grad student | 2014 | UC Berkeley |
| Falk Lieder | grad student | 2013-2018 | UC Berkeley (PsychTree) |
| Bill Thompson | post-doc | ||
| Qiong Zhang | post-doc | ||
| Robert D. Hawkins | post-doc | 2019- | Princeton |
BETA: Related publications
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Publications
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| Milli S, Lieder F, Griffiths TL. (2021) A rational reinterpretation of dual-process theories. Cognition. 217: 104881 |
| Gates V, Callaway F, Ho MK, et al. (2021) A rational model of people's inferences about others' preferences based on response times. Cognition. 217: 104885 |
| Hofman JM, Watts DJ, Athey S, et al. (2021) Integrating explanation and prediction in computational social science. Nature |
| Meylan SC, Griffiths TL. (2021) The Challenges of Large-Scale, Web-Based Language Datasets: Word Length and Predictability Revisited. Cognitive Science. 45: e12983 |
| Peterson JC, Bourgin DD, Agrawal M, et al. (2021) Using large-scale experiments and machine learning to discover theories of human decision-making. Science (New York, N.Y.). 372: 1209-1214 |
| Lewry C, Curtis K, Vasilyeva N, et al. (2021) Intuitions about magic track the development of intuitive physics. Cognition. 214: 104762 |
| Langlois TA, Jacoby N, Suchow JW, et al. (2021) Serial reproduction reveals the geometry of visuospatial representations. Proceedings of the National Academy of Sciences of the United States of America. 118 |
| Krafft PM, Shmueli E, Griffiths TL, et al. (2021) Bayesian collective learning emerges from heuristic social learning. Cognition. 212: 104469 |
| Callaway F, Rangel A, Griffiths TL. (2021) Fixation patterns in simple choice reflect optimal information sampling. Plos Computational Biology. 17: e1008863 |
| Battleday RM, Peterson JC, Griffiths TL. (2021) From convolutional neural networks to models of higher-level cognition (and back again). Annals of the New York Academy of Sciences |