| 2025 | CogSci | Investigating False Memory in the DRM Paradigm with Relational Category Content. | Alexus S. Longo, Kenneth J. Kurtz |
| 2025 | CogSci | Improving Category Learning through Graded Classification. | Mercury K. Mason, Kenneth J. Kurtz |
| 2024 | CogSci | Do People Know More Than Exemplar Models Would Predict? | Josh C. Glass, Kenneth J. Kurtz |
| 2024 | CogSci | Remembering better: A bridge between paired-associate learning and higher-order cognition. | Keith L. Sherman, Kenneth J. Kurtz |
| 2024 | CogSci | Abstracted Gaussian Prototypes for One-Shot Concept Learning. | Chelsea Zou, Kenneth J. Kurtz |
| 2023 | CogSci | Alternation as a Relational Category. | Josh C. Glass, Alexus S. Longo, Kenneth J. Kurtz |
| 2023 | CogSci | Modeling Human Performance on SHJ Category Structures with a Divergent Autoencoder. | Josh C. Glass, Mercury K. Mason, Kenneth J. Kurtz |
| 2023 | CogSci | Release from Proactive Interference with Relational Categories Versus Traditional Entity Categories. | Alexus S. Longo, Kenneth J. Kurtz |
| 2023 | CogSci | Sustaining Relational Preference in a Repeated Relational Match-to-Sample Task in the Absence of Task Support. | Mercury K. Mason, Kenneth J. Kurtz |
| 2023 | CogSci | Conceptual Integration and Semantic Relational Processing as Study Tasks to Promote Cued-Recall of Word Pairs. | Keith L. Sherman, Kenneth J. Kurtz |
| 2022 | CogSci | Local versus global coherence in the generalization of category training. | Josh C. Glass, Kenneth J. Kurtz |
| 2022 | CogSci | Investigating the impacts of an immersive learning mode and graded feedback on category learning. | Alexus S. Longo, Mercury K. Mason, Kenneth J. Kurtz |
| 2022 | CogSci | Examining Strategy Differences on the Relational Match-to-Sample Task (RMTS). | Mercury K. Mason, Kenneth J. Kurtz |
| 2022 | CogSci | Paths to Learning in Traditional Artificial Classification Tasks. | Keith L. Sherman, Kenneth J. Kurtz |
| 2021 | CogSci | Promoting Relational Responding: The Role of Prior Exposure to the Sample. | Mercury K. Mason, Kenneth J. Kurtz |
| 2021 | CogSci | Extrapolation Under Caricatured Representations. | Daniel Silliman, Kenneth J. Kurtz |
| 2021 | CogSci | Comparison Promotes the Spontaneous Transfer of Relational Categories. | Sean Snoddy, Kenneth J. Kurtz |
| 2020 | CogSci | Promoting relational responding by varying presentation conditions. | Mercury K. Mason, Kenneth J. Kurtz |
| 2020 | CogSci | Costly Exceptions: Deviant Exemplars Reduce Category Compression. | Daniel Silliman, Sean Snoddy, Matt Wetzel, Kenneth J. Kurtz |
| 2020 | CogSci | Analogical Transfer and Recognition Memory in Relational Classification Learning. | Sean Snoddy, Kenneth J. Kurtz |
| 2019 | CogSci | Warning: The Exemplars in Your Category Representation May Not Be the Ones Experienced During Learning. | Kenneth J. Kurtz, Daniel Silliman |
| 2019 | CogSci | Semi-supervised Learning with 2D Categories. | John D. Patterson, Kenneth J. Kurtz |
| 2019 | CogSci | Family Resemblance in Unsupervised Categorization: A Dissociation Between Production and Evaluation. | John D. Patterson, Sean Snoddy, Kenneth J. Kurtz |
| 2019 | CogSci | Introducing Recursive Linear Classification (RELIC) for Machine Learning. | Sean Snoddy, Kenneth J. Kurtz |
| 2018 | CogSci | Relational Categories: Why they're Important and How they are Learned. | 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 |
| 2018 | CogSci | Semi-supervised learning: A role for similarity in generalization-based learning of relational categories. | John D. Patterson, Kenneth J. Kurtz |
| 2018 | CogSci | What does a dimension that predicts nothing do to human classification learning? | Sean Snoddy, Kenneth J. Kurtz |
| 2018 | CogSci | Human generalization of an alternating category structure. | Matt Wetzel, Kenneth J. Kurtz |
| 2017 | CogSci | Object Understanding: Exploring the Path from Percept to Meaning. | Kenneth J. Kurtz, Daniel Silliman |
| 2017 | CogSci | Relational Concept Learning via Guided Interactive Discovery. | John D. Patterson, David Landy, Kenneth J. Kurtz |
| 2017 | CogSci | Promoting Spontaneous Analogical Transfer: The Role of Category Status. | Sean Snoddy, Kenneth J. Kurtz |
| 2016 | CogSci | Does Contrast or Comparison Help More? The Role of Learning Mode and Category Type. | Jan Andrews, Kenneth R. Livingston, Calais Larson, Kenneth J. Kurtz |
| 2016 | CogSci | Generalization of within-category feature correlations. | Nolan Conaway, Kenneth J. Kurtz |
| 2016 | CogSci | Switch it up: Learning Categories via Feature Switching. | Garrett Honke, Nolan Conaway, Kenneth J. Kurtz |
| 2016 | CogSci | Linear separability and human category learning: Revisiting a classic study. | Kimery R. Levering, Nolan Conaway, Kenneth J. Kurtz |
| 2016 | CogSci | Performance Pressure and Comparison in Relational Category Learning. | John D. Patterson, Kenneth J. Kurtz |
| 2016 | CogSci | Effects of Analogical Processing: Evidence for Re-representation. | Daniel Silliman, Kenneth J. Kurtz |
| 2016 | CogSci | The role of higher order relational structure in relational category label extension. | Sean Snoddy, Kenneth J. Kurtz |
| 2015 | CogSci | A Dissociation between Categorization and Similarity to Exemplars. | Nolan Conaway, Kenneth J. Kurtz |
| 2015 | CogSci | Exemplar models can't see the forest for the trees. | Nolan Conaway, Kenneth J. Kurtz |
| 2015 | CogSci | Learning mode and comparison in relational category learning. | John D. Patterson, Kenneth J. Kurtz |
| 2014 | CogSci | Now you know it, now you don't: Asking the right question about category knowledge. | Nolan Conaway, Kenneth J. Kurtz |
| 2014 | CogSci | Optimizing the category construction task to promote learning and transfer of knowledge in classroom instruction. | Kenneth J. Kurtz, Andy Cavagnetto, Garrett Honke, Nolan Conaway, John D. Patterson, James C. Marr, Yan Tao |
| 2014 | CogSci | Engaging the comparison engine: Implications for relational category learning and transfer. | John D. Patterson, Kenneth J. Kurtz |
| 2014 | CogSci | Brainprint: Identifying Unique Features of Neural Activity with Machine Learning. | Maria V. Ruiz-Blondet, Negin Khalifian, Blair C. Armstrong, Zhanpeng Jin, Kenneth J. Kurtz, Sarah Laszlo |
| 2013 | CogSci | Models of Human Category Learning: Do they Generalize? | Nolan Conaway, Kenneth J. Kurtz |
| 2013 | CogSci | Using Relational Encoding to Promote Creative Problem Solving. | Kenneth J. Kurtz, Nuoya Zhang, Tamar Skolnick |
| 2012 | CogSci | Observational category learning increases sensitivity to prototypical and correlational information. | Kimery R. Levering, Kenneth J. Kurtz |
| 2012 | GECCO | Evolving data sets to highlight the performance differences between machine learning classifiers. | Thomas Raway, J. David Schaffer, Kenneth J. Kurtz, Hiroki Sayama |
| 2011 | CogSci | Evaluating the Divergent Auto-Encoder (DIVA) as a Machine Learning Algorithm. | Kenneth J. Kurtz, Xavier Oyarzabal |
| 2011 | CogSci | Observational Category Learning as a Path to More Robust Generative Knowledge. | Kimery R. Levering, Kenneth J. Kurtz |
| 2011 | CogSci | Types of Cognitive Content and the Role of Relational Processing in the Illusion of Explanatory Depth. | Graham Silk-Eglit, Kenneth J. Kurtz |