Joseph Austerweil
TitleCited byYear
Multilevel coarse-to-fine PCFG parsing
E Charniak, M Johnson, M Elsner, J Austerweil, D Ellis, I Haxton, C Hill, ...
Proceedings of the main conference on Human Language Technology Conference …, 2006
702006
A unified local and global model for discourse coherence
M Elsner, J Austerweil, E Charniak
Human Language Technologies 2007: The Conference of the North American …, 2007
692007
Random Walks on Semantic Networks Can Resemble Optimal Foraging.
JT Abbott, JL Austerweil, TL Griffiths
Psychological Review 122 (3), 558-559, 2015
632015
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies
Y Jia, J Abbott, J Austerweil, T Griffiths, T Darrell
NIPS, 2013
432013
Seeking Confirmation Is Rational for Deterministic Hypotheses
JL Austerweil, TL Griffiths
Cognitive Science 35, 499-526, 2011
382011
Human memory search as a random walk in a semantic network
JT Abbott, JL Austerweil, TL Griffiths
Advances in Neural Information Processing Systems (Vol. 25), 2012
37*2012
Coordinate to cooperate or compete: abstract goals and joint intentions in social interaction
M Kleiman-Weiner, MK Ho, JL Austerweil, ML Littman, JB Tenenbaum
COGSCI, 2016
362016
Analyzing the history of Cognition using topic models
UC Priva, JL Austerweil
Cognition 135, 4-9, 2015
332015
A nonparametric Bayesian framework for constructing flexible feature representations.
JL Austerweil, TL Griffiths
Psychological Review 120 (4), 817-851, 2013
282013
The Sapir-Whorf hypothesis and probabilistic inference: Evidence from the domain of color
E Cibelli, Y Xu, JL Austerweil, TL Griffiths, T Regier
PloS one 11 (7), e0158725, 2016
272016
The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color
E Cibelli, Y Xu, JL Austerweil, TL Griffiths, T Regier
PLOS ONE 11 (7), e0158725, 2016
262016
Structure and flexibility in Bayesian models of cognition
JL Austerweil, SJ Gershman, JB Tenenbaum, TL Griffiths
Oxford Handbook of Computational and Mathematical Psychology. Oxford …, 2015
262015
Showing versus doing: Teaching by demonstration
MK Ho, M Littman, J MacGlashan, F Cushman, JL Austerweil
Advances In Neural Information Processing Systems, 3027-3035, 2016
252016
Analyzing human feature learning as nonparametric Bayesian inference.
JL Austerweil, TL Griffiths
NIPS, 97-104, 2008
23*2008
Examining Search Processes in Low and High Creative Individuals with Random Walks
YN Kenett, JL Austerweil
Cognitive Conference Society, 2016
212016
Networks of Social and Moral Norms in Human and Robot Agents
BF Malle, M Scheutz, JL Austerweil
A World with Robots, 3-17, 2017
192017
Constructing a hypothesis space from the Web for large-scale Bayesian word learning
JT Abbott, JL Austerweil, TL Griffiths
34th Annual Meeting of the Cognitive Science Society, 2012
192012
Learning hypothesis spaces and dimensions through concept learning
JL Austerweil, TL Griffiths
Proceedings of the 32nd Annual Conference of the Cognitive Science Society …, 2010
182010
Learning invariant features using the transformed Indian buffet process
JL Austerweil, TL Griffiths
Advances in neural information processing systems, 82-90, 2010
182010
A rational model of the effects of distributional information on feature learning
JL Austerweil, TL Griffiths
Cognitive Psychology 63 (4), 173-209, 2011
162011
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Articles 1–20