Joseph L. Austerweil

48 papers B 33Journal 6Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bayesian Event-Based Model for Disease Subtype and Stage Inference. CoRR Hongtao Hao, Joseph L. Austerweil
2025	J	`jnl`	Joint Progression Modeling (JPM): A Probabilistic Framework for Mixed-Pathology Progression. CoRR Hongtao Hao, Joseph L. Austerweil
2025	B	`conf`	Rethinking Rumination: A Decision-Theoretic Approach Without Negativity Bias. CogSci Michael Payton, Mary Vitello, Joseph L. Austerweil
2023	B	`conf`	Video games as a path to a contextualized cognitive science, or How to move beyond 20 questions with nature. CogSci George Kachergis, Joseph L. Austerweil
2021	B	`conf`	Cognitive Properties of Norm Representations. CogSci Bertram F. Malle, Joseph L. Austerweil, Vivienne Bihe Chi, Yoed N. Kenett, Emorie D. Beck, Stuti Thapa Magar, Mowafak Allaham
2021	B	`conf`	Inherence bias in explanation increases with age and cognitive impairment. CogSci Jeffrey C. Zemla, Blake H. Chambers, Joseph L. Austerweil, Andrei Cimpian
2021	B	`conf`	Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners. CogSci Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Jerry Zhu
2020	B	`conf`	Interactions Between Categorization and Intuitive Physics. CogSci Anantha Rao, Joseph L. Austerweil
2020	B	`conf`	The "Fraction Sense" Emerges from a Deep Convolutional Neural Network. CogSci Yun-Shiuan Chuang, Edward Hubbard, Joseph L. Austerweil
2020	J	`jnl`	Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners. CoRR Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu
2019	J	`jnl`	Analyzing Knowledge Retrieval Impairments Associated with Alzheimer's Disease Using Network Analyses. Complex. Jeffrey C. Zemla, Joseph L. Austerweil
2019	B	`conf`	Evaluating Theories of Collaborative Cognition Using the Hawkes Process and a Large Naturalistic Data Set. CogSci Mohsen Afrasiabi, Mark G. Orr, Joseph L. Austerweil
2019	J	`jnl`	Learning How to Generalize. Cogn. Sci. Joseph L. Austerweil, Sophia Sanborn, Thomas L. Griffiths
2019	B	`conf`	Novel categories are distinct from "Not"-categories. CogSci Shi Xian Liew, Joseph L. Austerweil
2019	B	`conf`	Subjective Randomness in a Non-cooperative Game. CogSci Michael Payton, Jeffrey C. Zemla, Joseph L. Austerweil
2018	B	`conf`	Bayesian Generalization of Emojis. CogSci Jacqueline Erens, Joseph L. Austerweil
2018	B	`conf`	Do Humans Navigate via Random Walks? Modeling Navigation in a Semantic Word Game. CogSci Mohammad Isyroqi Fathan, Eli K. Renfro, Joseph L. Austerweil, Nicole M. Beckage
2018	B	`conf`	Effectively Learning from Pedagogical Demonstrations. CogSci Mark K. Ho, Michael L. Littman, Fiery Cushman, Joseph L. Austerweil
2018	B	`conf`	Possible Mechanisms of Bilingual Advantage on Creativity. CogSci Kendra Lange, Elise Hopman, Elizabeth Pettit, Anantha Rao, Nicole M. Beckage, Jeffrey C. Zemla, Joseph L. Austerweil
2018	B	`conf`	Predictors of L2 word learning accuracy: A big data investigation. CogSci Elise Hopman, Bill Thompson, Joseph L. Austerweil, Gary Lupyan
2018	B	`conf`	Rapid Learning in Early Attentional Processing: Bayesian Estimation of Trial-by-Trial Updating. CogSci Aaron Cochrane, Joseph L. Austerweil, Vanessa R. Simmering, C. Shawn Green
2017	B	`conf`	Interpreting Asymmetric Perception in Speech Perception with Bayesian Inference. CogSci Jie Ren, Joseph L. Austerweil
2017	B	`conf`	Mental Representations and Computational Modeling of Context-Specific Human Norm Systems. CogSci Vasanth Sarathy, Matthias Scheutz, Yoed N. Kenett, Mowafak Allaham, Joseph L. Austerweil, Bertram F. Malle
2017	B	`conf`	Modeling Semantic Fluency Data as Search on a Semantic Network. CogSci Jeffrey C. Zemla, Joseph L. Austerweil
2017	B	`conf`	PACKER: An Exemplar Model of Category Generation. CogSci Nolan Conaway, Joseph L. Austerweil
2017	B	`conf`	Teaching by Intervention: Working Backwards, Undoing Mistakes, or Correcting Mistakes? CogSci Mark K. Ho, Michael L. Littman, Joseph L. Austerweil
2016	B	`conf`	Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction. CogSci Max Kleiman-Weiner, Mark K. Ho, Joseph L. Austerweil, Michael L. Littman, Josh Tenenbaum
2016	B	`conf`	Examining Search Processes in Low and High Creative Individuals with Random Walks. CogSci Yoed N. Kenett, Joseph L. Austerweil
2016	B	`conf`	Feature-based Joint Planning and Norm Learning in Collaborative Games. CogSci Mark K. Ho, James MacGlashan, Amy Greenwald, Michael L. Littman, Elizabeth Hilliard, Carl Trimbach, Stephen Brawner, Josh Tenenbaum, Max Kleiman-Weiner, Joseph L. Austerweil
2016	—	`conf`	Showing versus doing: Teaching by demonstration. NIPS Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Cushman, Joseph L. Austerweil
2016	B	`conf`	The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color. CogSci Emily Cibelli, Yang Xu, Joseph L. Austerweil, Thomas L. Griffiths, Terry Regier
2016	B	`conf`	The construction of function representations. CogSci Brian Montambault, Christopher Lucas, Joseph L. Austerweil
2016	B	`conf`	U-INVITE: Estimating Individual Semantic Networks from Fluency Data. CogSci Jeffrey C. Zemla, Yoed N. Kenett, Kwang-Sung Jun, Joseph L. Austerweil
2015	B	`conf`	Learning Additive and Substitutive Features. CogSci Ting Qian, Joseph L. Austerweil
2015	B	`conf`	Teaching with Rewards and Punishments: Reinforcement or Communication? CogSci Mark K. Ho, Michael L. Littman, Fiery Cushman, Joseph L. Austerweil
2014	B	`conf`	Testing the psychological validity of cluster construction biases. CogSci Joseph L. Austerweil
2013	—	`conf`	Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies. NIPS Yangqing Jia, Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths, Trevor Darrell
2012	B	`conf`	Comparing the inductive biases of simple neural networks and Bayesian models. CogSci Thomas L. Griffiths, Joseph L. Austerweil, Vincent G. Berthiaume
2012	B	`conf`	Constructing a hypothesis space from the Web for large-scale Bayesian word learning. CogSci Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths
2012	—	`—`	Constructing flexible feature representations using nonparametric Bayesian inference Joseph L. Austerweil
2012	—	`conf`	Human memory search as a random walk in a semantic network. NIPS Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths
2011	—	`conf`	An ideal observer model for identifying the reference frame of objects. NIPS Joseph L. Austerweil, Abram L. Friesen, Thomas L. Griffiths
2011	B	`conf`	Grow your own representations: Computational constructivism. CogSci Joseph L. Austerweil, Thomas L. Griffiths, Todd M. Gureckis, Robert L. Goldstone, Kevin Robert Canini, Matt Jones
2011	J	`jnl`	Seeking Confirmation Is Rational for Deterministic Hypotheses. Cogn. Sci. Joseph L. Austerweil, Thomas L. Griffiths
2010	—	`conf`	Learning invariant features using the Transformed Indian Buffet Process. NIPS Joseph L. Austerweil, Thomas L. Griffiths
2008	—	`conf`	Analyzing human feature learning as nonparametric Bayesian inference. NIPS Joseph L. Austerweil, Thomas L. Griffiths
2007	—	`conf`	A Unified Local and Global Model for Discourse Coherence. HLT-NAACL Micha Elsner, Joseph L. Austerweil, Eugene Charniak
2006	—	`conf`	Multilevel Coarse-to-Fine PCFG Parsing. HLT-NAACL Eugene Charniak, Mark Johnson, Micha Elsner, Joseph L. Austerweil, David A. Ellis, Isaac Haxton, Catherine Hill, R. Shrivaths, Jeremy Moore, Michael Pozar, Theresa Vu