Daniel J. Navarro

Publication Activity (10 Years)

Years Active: 2000-2017
Publications (10 Years): 14

Top Topics

Inductive Inference

Decision Processes

Hypothesis Spaces

Top Venues

Top. Cogn. Sci.

Publications

Daniel J. Navarro, Amy Perfors, Arthur Kary, Scott Brown, Christopher Donkin
When extremists win: On the behavior of iterated learning chains when priors are heterogeneous. CogSci (2017)
Lauren Kennedy, Amy Perfors, Daniel J. Navarro
Priors, informative cues and ambiguity aversion. CogSci (2017)
Brett K. Hayes, Stephanie Banner, Daniel J. Navarro
Sampling frames, Bayesian inference and inductive reasoning. CogSci (2017)
Steven Langsford, Andrew Hendrickson, Amy Perfors, Daniel J. Navarro
When do learned transformations influence similarity and categorization? CogSci (2017)
Keith Ransom, Wouter Voorspoels, Amy Perfors, Daniel J. Navarro
A cognitive analysis of deception without lying. CogSci (2017)
Simon De Deyne, Amy Perfors, Daniel J. Navarro
Predicting Human Similarity Judgments with Distributional Models: The Value of Word Associations. IJCAI (2017)
Wai Keen Vong, Andrew Hendrickson, Amy Perfors, Daniel J. Navarro
Do additional features help or harm during category learning? An exploration of the curse of dimensionality in human learners. CogSci (2016)
Keith Ransom, Amy Perfors, Daniel J. Navarro
Leaping to Conclusions: Why Premise Relevance Affects Argument Strength. Cogn. Sci. 40 (7) (2016)
Matthew Welsh, Sandy Steacy, Steve Begg, Daniel J. Navarro
A Tale of Two Disasters: Biases in Risk Communication. CogSci (2016)
Simon De Deyne, Amy Perfors, Daniel J. Navarro
Predicting human similarity judgments with distributional models: The value of word associations. COLING (2016)
Keith Ransom, Wouter Voorspoels, Amy Perfors, Daniel J. Navarro
Sensitivity to communicative norms when deceiving without lying. CogSci (2015)
Simon De Deyne, Steven Verheyen, Amy Perfors, Daniel J. Navarro
Evidence for widespread thematic structure in the mental lexicon. CogSci (2015)
Wouter Voorspoels, Daniel J. Navarro, Amy Perfors, Keith Ransom
Gricean maxims influence inductive inference with negative observations. CogSci (2015)
Andrew Hendrickson, Daniel J. Navarro, Christopher Donkin
Quantifying the time course of similarity. CogSci (2015)
Sean Tauber, Daniel J. Navarro, Amy Perfors, Michael D. Lee
Inferring the hypothesis spaces underlying inductive generalization. CogSci (2014)
Andrew Hendrickson, Amy Perfors, Daniel J. Navarro
Adaptive information source selection during hypothesis testing. CogSci (2014)
Amy Perfors, Daniel J. Navarro
Language Evolution Can Be Shaped by the Structure of the World. Cogn. Sci. 38 (4) (2014)
Daniel J. Navarro, Ben R. Newell
Information versus reward in a changing world. CogSci (2014)
Wai Keen Vong, Amy Perfors, Daniel J. Navarro
The relevance of labels in semi-supervised learning depends on category structure. CogSci (2014)
Amy Perfors, Keith Ransom, Daniel J. Navarro
People ignore token frequency when deciding how widely to generalize. CogSci (2014)
Steven Langsford, Andrew Hendrickson, Amy Perfors, Daniel J. Navarro
People are sensitive to hypothesis sparsity during category discrimination. CogSci (2014)
Ian G. Fuss, Daniel J. Navarro
Open Parallel Cooperative and Competitive Decision Processes: A Potential Provenance for Quantum Probability Decision Models. Top. Cogn. Sci. 5 (4) (2013)
Wai Keen Vong, Andrew Hendrickson, Amy Perfors, Daniel J. Navarro
The role of sampling assumptions in generalization with multiple categories. CogSci (2013)
Simon De Deyne, Daniel J. Navarro, Gert Storms
Associative strength and semantic activation in the mental lexicon: evidence from continued word associations. CogSci (2013)
Daniel J. Navarro
Finding hidden types: Inductive inference in long-tailed environments. CogSci (2013)
Simon De Deyne, Daniel J. Navarro, Amy Perfors, Gert Storms
Strong structure in weak semantic similarity: A graph based account. CogSci (2012)
Daniel J. Navarro, Matthew J. Dry, Michael D. Lee
Sampling Assumptions in Inductive Generalization. Cogn. Sci. 36 (2) (2012)
Daniel J. Navarro, Amy Perfors
Anticipating changes: Adaptation and extrapolation in category learning. CogSci (2012)
Marcus A. Butavicius, Michael D. Lee, Brandon M. Pincombe, Louise G. Mullen, Daniel J. Navarro, Kathryn Parsons, Agata McCormac
An assessment of email and spontaneous dialog visualizations. Int. J. Hum. Comput. Stud. 70 (6) (2012)
Matthew Welsh, Daniel J. Navarro, Steve Begg
Number Preference, Precision and Implicit Confidence. CogSci (2011)
Amy Perfors, Daniel J. Navarro
Language evolution is shaped by the structure of the world: An iterated learning analysis. CogSci (2011)
Belinda Bruza, Matthew Welsh, Daniel J. Navarro, Steve Begg
Does anchoring cause overconfidence only in experts? CogSci (2011)
Robert Montague, Daniel J. Navarro, Amy Perfors, Russell Warner, Patrick Shafto
To catch a liar: The effects of truthful and deceptive testimony on inferential learning. CogSci (2011)
Dinis Gökaydin, Anna Ma-Wyatt, Daniel J. Navarro, Amy Perfors
Humans use different statistics for sequence analysis depending on the task. CogSci (2011)
Simon De Deyne, Wouter Voorspoels, Steven Verheyen, Daniel J. Navarro, Gert Storms
Graded structure in adjective categories. CogSci (2011)
Luke Maurits, Daniel J. Navarro, Amy Perfors
Why are some word orders more common than others? A uniform information density account. NIPS (2010)
Daniel J. Navarro
Learning the context of a category. NIPS (2010)
Amy L. Walwyn, Daniel J. Navarro
Minimal Paths in the City Block: Human Performance on Euclidean and Non-Euclidean Traveling Salesperson Problems. J. Probl. Solving 3 (1) (2010)
Daniel J. Navarro, Thomas L. Griffiths
Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach. Neural Comput. 20 (11) (2008)
Daniel J. Navarro, Thomas L. Griffiths
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments. NIPS (2006)
Michael D. Lee, Ian G. Fuss, Daniel J. Navarro
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time. NIPS (2006)
Jay I. Myung, Mark A. Pitt, Daniel J. Navarro
Model selection in cognitive science as an inverse problem. Computational Imaging (2005)
Daniel J. Navarro, Michael D. Lee
An application of minimum description length clustering to partitioning learning curves. ISIT (2005)
Daniel J. Navarro
A Note on the Applied Use of MDL Approximations. Neural Comput. 16 (9) (2004)
Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science. NIPS (2003)
Daniel J. Navarro, Michael D. Lee
Combining Dimensions and Features in Similarity-Based Representations. NIPS (2002)
Douglas Vickers, Daniel J. Navarro, Michael D. Lee
Towards a transformational approach to perceptual organization. KES (2000)