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Conference and Workshop Papers
- 2021
[c10]Sean Snoddy, Kenneth J. Kurtz:
Comparison Promotes the Spontaneous Transfer of Relational Categories. CogSci 2021- 2020
- [c9]Daniel Silliman, Sean Snoddy, Matt Wetzel, Kenneth J. Kurtz:
Costly Exceptions: Deviant Exemplars Reduce Category Compression. CogSci 2020 - [c8]Sean Snoddy, Kenneth J. Kurtz:
Analogical Transfer and Recognition Memory in Relational Classification Learning. CogSci 2020 - 2019
- [c7]John D. Patterson, Sean Snoddy, Kenneth J. Kurtz:
Family Resemblance in Unsupervised Categorization: A Dissociation Between Production and Evaluation. CogSci 2019: 2537-2543 - [c6]Sean Snoddy, Joseph Wilson, Daniel Silliman, Kenneth Houghton, Deanne Westerman:
It's Alive! Animate Sources Produce Mnemonic Benefits. CogSci 2019: 2831-2838 - [c5]Sean Snoddy, Kenneth J. Kurtz:
Introducing Recursive Linear Classification (RELIC) for Machine Learning. CogSci 2019: 3576 - 2018
- [c4]Dedre Gentner, Nina Simms, Kenneth J. Kurtz, Garrett Honke, Sean Snoddy, Kenneth D. Forbus, Lindsey E. Richland, Bryan J. Matlen, Emily McLaughlin Lyons, Ellen C. Klostermann:
Relational Categories: Why they're Important and How they are Learned. CogSci 2018 - [c3]Sean Snoddy, Kenneth J. Kurtz:
What does a dimension that predicts nothing do to human classification learning? CogSci 2018 - 2017
- [c2]Sean Snoddy, Kenneth J. Kurtz:
Promoting Spontaneous Analogical Transfer: The Role of Category Status. CogSci 2017 - 2016
- [c1]Sean Snoddy, Kenneth J. Kurtz:
The role of higher order relational structure in relational category label extension. CogSci 2016
Coauthor Index
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