All Topics
Foundations
Perception
Education
Causal Induction
Cognitive Development
Probabilistic Reasoning
Rational Process Models
Similarity and Categorization
Statistical Models of Language
Nonparametric Bayesian Models
Cultural Evolution and Iterated Learning
Decision Making and Reinforcement Learning
(Click on an author's name to view all papers by that author.)
By Peterson, J | |
| Battleday, R. M., Peterson, J. C., & Griffiths, T. L. (preprint). Modeling human categorization of natural images using deep feature representations. (link) |
| Peterson, J. C., Abbott, J. T., & Griffiths, T. L. (in press). Evaluating (and improving) the correspondence between deep neural networks and human representations. Cognitive Science. (pdf) |
| Peterson, J. C., Suchow, J. W., Aghi, K., Ku, A. Y., & Griffiths, T. L. (2018). Capturing human category representations by sampling in deep feature spaces. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf) |
| Suchow, J. W., Peterson, J. C., & Griffiths, T. L. (2018). Learning a face space for experiments on human identity. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf) |
| Peterson, J. C., Soulos, P., Nematzadeh, A., & Griffiths, T. L. (2018). Learning hierarchical visual representations in deep neural networks using hierarchical linguistic labels. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pdf) |
| Chen, D., Peterson, J. C., & Griffiths, T. L. (2017). Evaluating vector-space models of analogy. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf) |
| Peterson, J. C., & Griffiths, T. L. (2017). Evidence for the size principle in semantic and perceptual domains. Proceedings of the 39th Annual Conference of the Cognitive Science Society. (pdf) |
| Peterson, J., Abbott, J. T., & Griffiths, T. L. (2016). Adapting deep network features to capture psychological representations. Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pdf) (Winner of the Computational Modeling Prize in Perception/Action) |