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ORCIDJoseph L. Austerweil
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- affiliation: University of Wisconsin, Madison, WI, US
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2020 – today
- 2023
[c40]George Kachergis, Joseph L. Austerweil:
Video games as a path to a contextualized cognitive science, or How to move beyond 20 questions with nature. CogSci 2023- 2021
- [c39]Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Jerry Zhu:
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners. CogSci 2021 - [c38]Bertram F. Malle, Joseph L. Austerweil, Vivienne Bihe Chi, Yoed N. Kenett, Emorie D. Beck, Stuti Thapa Magar, Mowafak Allaham:
Cognitive Properties of Norm Representations. CogSci 2021 - [c37]Jeffrey C. Zemla, Blake H. Chambers, Joseph L. Austerweil, Andrei Cimpian:
Inherence bias in explanation increases with age and cognitive impairment. CogSci 2021 - 2020
- [c36]Yun-Shiuan Chuang, Edward Hubbard, Joseph L. Austerweil:
The "Fraction Sense" Emerges from a Deep Convolutional Neural Network. CogSci 2020 - [c35]Anantha Rao, Joseph L. Austerweil:
Interactions Between Categorization and Intuitive Physics. CogSci 2020 - [i1]Yun-Shiuan Chuang
, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu:
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners. CoRR abs/2009.02476 (2020)
2010 – 2019
- 2019
- [j3]Joseph L. Austerweil, Sophia Sanborn, Thomas L. Griffiths:
Learning How to Generalize. Cogn. Sci. 43(8) (2019) - [j2]Jeffrey C. Zemla, Joseph L. Austerweil:
Analyzing Knowledge Retrieval Impairments Associated with Alzheimer's Disease Using Network Analyses. Complex. 2019: 4203158:1-4203158:12 (2019) - [c34]Mohsen Afrasiabi, Mark G. Orr, Joseph L. Austerweil:
Evaluating Theories of Collaborative Cognition Using the Hawkes Process and a Large Naturalistic Data Set. CogSci 2019: 69-75 - [c33]Shi Xian Liew, Joseph L. Austerweil:
Novel categories are distinct from "Not"-categories. CogSci 2019: 2147-2153 - [c32]Michael Payton, Jeffrey C. Zemla, Joseph L. Austerweil:
Subjective Randomness in a Non-cooperative Game. CogSci 2019: 2544-2549 - 2018
- [c31]Aaron Cochrane, Joseph L. Austerweil, Vanessa R. Simmering, C. Shawn Green:
Rapid Learning in Early Attentional Processing: Bayesian Estimation of Trial-by-Trial Updating. CogSci 2018 - [c30]Jacqueline Erens, Joseph L. Austerweil:
Bayesian Generalization of Emojis. CogSci 2018 - [c29]Mohammad Isyroqi Fathan, Eli K. Renfro, Joseph L. Austerweil, Nicole M. Beckage:
Do Humans Navigate via Random Walks? Modeling Navigation in a Semantic Word Game. CogSci 2018 - [c28]Mark K. Ho, Michael L. Littman, Fiery Cushman, Joseph L. Austerweil:
Effectively Learning from Pedagogical Demonstrations. CogSci 2018 - [c27]Elise Hopman, Bill Thompson, Joseph L. Austerweil, Gary Lupyan:
Predictors of L2 word learning accuracy: A big data investigation. CogSci 2018 - [c26]Kendra Lange, Elise Hopman, Elizabeth Pettit, Anantha Rao, Nicole M. Beckage, Jeffrey C. Zemla, Joseph L. Austerweil:
Possible Mechanisms of Bilingual Advantage on Creativity. CogSci 2018 - 2017
- [c25]Nolan Conaway, Joseph L. Austerweil:
PACKER: An Exemplar Model of Category Generation. CogSci 2017 - [c24]Mark K. Ho, Michael L. Littman, Joseph L. Austerweil:
Teaching by Intervention: Working Backwards, Undoing Mistakes, or Correcting Mistakes? CogSci 2017 - [c23]Jie Ren, Joseph L. Austerweil:
Interpreting Asymmetric Perception in Speech Perception with Bayesian Inference. CogSci 2017 - [c22]Vasanth Sarathy, Matthias Scheutz, Yoed N. Kenett, Mowafak Allaham, Joseph L. Austerweil, Bertram F. Malle:
Mental Representations and Computational Modeling of Context-Specific Human Norm Systems. CogSci 2017 - [c21]Jeffrey C. Zemla, Joseph L. Austerweil:
Modeling Semantic Fluency Data as Search on a Semantic Network. CogSci 2017 - 2016
- [c20]Emily Cibelli, Yang Xu, Joseph L. Austerweil, Thomas L. Griffiths, Terry Regier:
The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color. CogSci 2016 - [c19]Mark K. Ho, James MacGlashan, Amy Greenwald, Michael L. Littman, Elizabeth Hilliard, Carl Trimbach, Stephen Brawner, Josh Tenenbaum, Max Kleiman-Weiner, Joseph L. Austerweil:
Feature-based Joint Planning and Norm Learning in Collaborative Games. CogSci 2016 - [c18]Yoed N. Kenett, Joseph L. Austerweil:
Examining Search Processes in Low and High Creative Individuals with Random Walks. CogSci 2016 - [c17]Max Kleiman-Weiner, Mark K. Ho, Joseph L. Austerweil, Michael L. Littman, Josh Tenenbaum:
Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction. CogSci 2016 - [c16]Brian Montambault, Christopher Lucas, Joseph L. Austerweil:
The construction of function representations. CogSci 2016 - [c15]Jeffrey C. Zemla, Yoed N. Kenett, Kwang-Sung Jun, Joseph L. Austerweil:
U-INVITE: Estimating Individual Semantic Networks from Fluency Data. CogSci 2016 - [c14]Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Cushman, Joseph L. Austerweil:
Showing versus doing: Teaching by demonstration. NIPS 2016: 3027-3035 - 2015
- [c13]Mark K. Ho, Michael L. Littman, Fiery Cushman, Joseph L. Austerweil:
Teaching with Rewards and Punishments: Reinforcement or Communication? CogSci 2015 - [c12]Ting Qian, Joseph L. Austerweil:
Learning Additive and Substitutive Features. CogSci 2015 - 2014
- [c11]Joseph L. Austerweil:
Testing the psychological validity of cluster construction biases. CogSci 2014 - 2013
- [c10]Yangqing Jia, Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths, Trevor Darrell:
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies. NIPS 2013: 1842-1850 - 2012
- [b1]Joseph L. Austerweil:
Constructing flexible feature representations using nonparametric Bayesian inference. University of California, Berkeley, USA, 2012 - [c9]Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths:
Constructing a hypothesis space from the Web for large-scale Bayesian word learning. CogSci 2012 - [c8]Thomas L. Griffiths, Joseph L. Austerweil, Vincent G. Berthiaume:
Comparing the inductive biases of simple neural networks and Bayesian models. CogSci 2012 - [c7]Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths:
Human memory search as a random walk in a semantic network. NIPS 2012: 3050-3058 - 2011
- [j1]Joseph L. Austerweil, Thomas L. Griffiths:
Seeking Confirmation Is Rational for Deterministic Hypotheses. Cogn. Sci. 35(3): 499-526 (2011) - [c6]Joseph L. Austerweil, Thomas L. Griffiths, Todd M. Gureckis, Robert L. Goldstone, Kevin Robert Canini, Matt Jones:
Grow your own representations: Computational constructivism. CogSci 2011 - [c5]Joseph L. Austerweil, Abram L. Friesen, Thomas L. Griffiths:
An ideal observer model for identifying the reference frame of objects. NIPS 2011: 514-522 - 2010
- [c4]Joseph L. Austerweil, Thomas L. Griffiths:
Learning invariant features using the Transformed Indian Buffet Process. NIPS 2010: 82-90
2000 – 2009
- 2008
- [c3]Joseph L. Austerweil, Thomas L. Griffiths:
Analyzing human feature learning as nonparametric Bayesian inference. NIPS 2008: 97-104 - 2007
- [c2]Micha Elsner, Joseph L. Austerweil, Eugene Charniak:
A Unified Local and Global Model for Discourse Coherence. HLT-NAACL 2007: 436-443 - 2006
- [c1]Eugene Charniak, Mark Johnson, Micha Elsner, Joseph L. Austerweil, David A. Ellis, Isaac Haxton, Catherine Hill, R. Shrivaths, Jeremy Moore, Michael Pozar, Theresa Vu:
Multilevel Coarse-to-Fine PCFG Parsing. HLT-NAACL 2006
Coauthor Index
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