Joseph Austerweil

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Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityVerified email at princeton.edu
Fiery CushmanPsychology, Harvard UniversityVerified email at fas.harvard.edu
Joshua T. AbbottUniversity of California, BerkeleyVerified email at berkeley.edu
Jeffrey C. ZemlaSyracuse UniversityVerified email at syr.edu
Joshua B. TenenbaumMITVerified email at mit.edu
Yoed N. KenettTechnion - Israel Institute of TechnologyVerified email at technion.ac.il
Micha ElsnerAssistant Professor of Linguistics, The Ohio State UniversityVerified email at ling.ohio-state.edu
Eugene CharniakProfessor of Computer Science, Brown UniversityVerified email at brown.edu
Max Kleiman-WeinerHarvard & MITVerified email at mit.edu
Bertram MalleBrown UniversityVerified email at brown.edu
Yangqing JiaVP, Alibaba GroupVerified email at daggerfs.com
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyVerified email at eecs.berkeley.edu
Amy GreenwaldProfessor of Computer Science, Brown UniversityVerified email at brown.edu
Matthias ScheutzProfessor of Computer Science and Cognitive Science, Tufts UniversityVerified email at tufts.edu
Emily CibelliData Scientist, PicnicHealthVerified email at berkeley.edu
Cohen Priva, UrielBrown UniversityVerified email at brown.edu
Mowafak AllahamNorthwestern UniversityVerified email at u.northwestern.edu
Stephen E. PalmerU.C. BerkeleyVerified email at berkeley.edu
Samuel GershmanProfessor, Harvard UniversityVerified email at fas.harvard.edu
Kwang-Sung JunThe University of ArizonaVerified email at cs.arizona.edu

Joseph Austerweil

Associate Professor at University of Wisconsin-Madison

Verified email at wisc.edu - Homepage

Computational cognitive science Inductive Inference knowledge representation Categorization Nonparametric Bayesian Methods


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Random Walks on Semantic Networks Can Resemble Optimal Foraging. JT Abbott, JL Austerweil, TL Griffiths Psychological Review 122 (3), 558-559, 2015	158	2015
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	137	2016
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	99	2016
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	95	2007
New perspectives on the aging lexicon DU Wulff, S De Deyne, MN Jones, R Mata, Aging Lexicon Consortium Trends in cognitive sciences 23 (8), 686-698, 2019	93	2019
Seeking Confirmation Is Rational for Deterministic Hypotheses JL Austerweil, TL Griffiths Cognitive Science 35, 499-526, 2011	83	2011
Multilevel coarse-to-fine PCFG parsing E Charniak, M Johnson, M Elsner, J Austerweil, D Ellis, I Haxton, C Hill, ... Proceedings of the Human Language Technology Conference of the NAACL, Main …, 2006	82	2006
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	79	2016
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	79	2016
Analyzing the history of Cognition using topic models UC Priva, JL Austerweil Cognition 135, 4-9, 2015	69	2015
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies Y Jia, J Abbott, J Austerweil, T Griffiths, T Darrell NIPS, 2013	69	2013
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	64*	2012
Networks of Social and Moral Norms in Human and Robot Agents BF Malle, M Scheutz, JL Austerweil A World with Robots, 3-17, 2017	59	2017
Estimating semantic networks of groups and individuals from fluency data JC Zemla, JL Austerweil Computational Brain & Behavior 1 (1), 36-58, 2018	49	2018
A nonparametric Bayesian framework for constructing flexible feature representations. JL Austerweil, TL Griffiths Psychological Review 120 (4), 817-851, 2013	47	2013
Examining Search Processes in Low and High Creative Individuals with Random Walks YN Kenett, JL Austerweil Cognitive Conference Society, 2016	46	2016
Teaching with Rewards and Punishments: Reinforcement or Communication? MK Ho, ML Littman, F Cushman, JL Austerweil Annual Proceedings of the 37th Cognitive Science Society Meeting, 2015	41	2015
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	39	2015
Feature-based Joint Planning and Norm Learning in Collaborative Games MK Ho, J MacGlashan, A Greenwald, ML Littman, EM Hilliard, C Trimbach, ... Annual Conference of the Cognitive Science Society, 2016	38	2016
People teach with rewards and punishments as communication, not reinforcements. MK Ho, F Cushman, ML Littman, JL Austerweil Journal of Experimental Psychology: General 148 (3), 520, 2019	37	2019

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