John E. Hummel

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 8

Top Topics

Learning Models

Cross Domain Text Classification

Probabilistic Relational

Explicitly Represented

Top Venues

Cogn. Syst. Res.

Publications

Valerio Biscione, Dong Yin, Gaurav Malhotra, Marin Dujmovic, Milton Llera Montero, Guillermo Puebla, Federico Adolfi, Rachel F. Heaton, John E. Hummel, Benjamin D. Evans, Karim Habashy, Jeffrey S. Bowers
MindSet: Vision. A toolbox for testing DNNs on key psychological experiments. CoRR (2024)
Jeffrey S. Bowers, Gaurav Malhotra, Federico Adolfi, Marin Dujmovic, Milton Llera Montero, Valerio Biscione, Guillermo Puebla, John E. Hummel, Rachel Heaton
On the importance of severely testing deep learning models of cognition. Cogn. Syst. Res. 82 (2023)
Yuhui Du, John E. Hummel, Alexander A. Petrov
Exaggeration of Stimulus Attributes in the Representation of Relational Categories. CogSci (2022)
Yuhui Du, John E. Hummel, Alexander A. Petrov
Probing the Mental Representation of Relation-Defined Categories. CogSci (2021)
Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin, John E. Hummel
Relation learning in a neurocomputational architecture supports cross-domain transfer. CogSci (2020)
Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin, John E. Hummel
Relation learning in a neurocomputational architecture supports cross-domain transfer. CoRR (2019)
Sean Wilner, John E. Hummel
Automating the Encoding for the LISA Model of Analogy from Raw Text. MAICS (2017)
Wookyoung Jung, John E. Hummel
Making Probabilistic Relational Categories Learnable. Cogn. Sci. 39 (6) (2015)
Wookyoung Jung, John E. Hummel
The effects of dual verbal and visual tasks on featural vs. relational category learning. CogSci (2013)
Wookyoung Jung, John E. Hummel
Hierarchical Category Structures Facilitate Acquisition of Probabilistic Relational Categories. CogSci (2012)
John E. Hummel
Getting symbols out of a neural architecture. Connect. Sci. 23 (2) (2011)
Wookyoung Jung, John E. Hummel
Progressive Alignment Facilitates Learning of Deterministic But Not Probabilistic Relational Categories. CogSci (2011)
Eric G. Taylor, John E. Hummel
Corrigendum to "Finding similarity in a model of relational reasoning" [Cognitive Systems Research 10 (2009) 229-239]. Cogn. Syst. Res. 11 (2) (2010)
John E. Hummel
Symbolic Versus Associative Learning. Cogn. Sci. 34 (6) (2010)
Leonidas A. A. Doumas, John E. Hummel
A Computational Account of the Development of the Generalization of Shape Information. Cogn. Sci. 34 (4) (2010)
Eric G. Taylor, John E. Hummel
Finding similarity in a model of relational reasoning. Cogn. Syst. Res. 10 (3) (2009)
John E. Hummel, David H. Landy, Derek Devnich
Toward a Process Model of Explanation with Implications for the Type-Token Problem. AAAI Fall Symposium: Naturally-Inspired Artificial Intelligence (2008)
Daniel C. Krawczyk, Keith J. Holyoak, John E. Hummel
The One-to-One Constraint in Analogical Mapping and Inference. Cogn. Sci. 29 (5) (2005)
John E. Hummel, Keith J. Holyoak, Collin B. Green, Leonidas A. A. Doumas, Derek Devnich, Aniket Kittur, Donald J. Kalar
A Solution to the Binding Problem for Compositional Connectionism. AAAI Technical Report (3) (2004)
James K. Kroger, Keith J. Holyoak, John E. Hummel
Varieties of sameness: the impact of relational complexity on perceptual comparisons. Cogn. Sci. 28 (3) (2004)
John E. Hummel
"Effective systematicity" in, "effective systematicity" out: a reply to Edelman and Intrator (2003). Cogn. Sci. 27 (2) (2003)
Irving Biederman, Eric Cooper, John E. Hummel, József Fiser
Geon Theory as an Account of Shape Recognition in Mind, Brain and Machine. BMVC (1993)