Amy Perfors

发表

How recursive is language? A Bayesian exploration

Joshua B. Tenenbaum, Amy Perfors, Edward Gibson, 2010 .

Representations, approximations, and limitations within a computational framework for cognitive science. Comment on "Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition" by W. Tecumseh Fitch.

Amy Perfors, 2014, Physics of life reviews.

Leaping to Conclusions: Why Premise Relevance Affects Argument Strength

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2016, Cogn. Sci..

Sample size, number of categories and sampling assumptions: Exploring some differences between categorization and generalization

Danielle J. Navarro, Amy Perfors, Keith Ransom, 2019, Cognitive Psychology.

When extremists win: On the behavior of iterated learning chains when priors are heterogeneous

Amy Perfors, Daniel J. Navarro, Scott Brown, 2017, CogSci.

Musicians are better at learning non-native sound contrasts even in non-tonal languages

Amy Perfors, Jia Hoong Ong, J. Ong, 2012, CogSci.

Gricean maxims influence inductive inference with negative observations

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2015, CogSci.

Language evolution is shaped by the structure of the world: An iterated learning analysis

Amy Perfors, Daniel J. Navarro, D. Navarro, 2011, CogSci.

Not every credible interval is credible: Evaluating robustness in the presence of contamination in Bayesian data analysis

Amy Perfors, Lauren A Kennedy, Daniel J Navarro, 2017, Behavior research methods.

Language Evolution Can Be Shaped by the Structure of the World

Amy Perfors, Daniel J. Navarro, D. Navarro, 2014, Cogn. Sci..

Priors, informative cues and ambiguity aversion

Amy Perfors, Daniel J. Navarro, Lauren Kennedy, 2017, CogSci.

Probability matching vs over-regularization in language: Participant behavior depends on their interpretation of the task

Amy Perfors, 2012, CogSci.

Generic noun phrases in child speech

Amy Perfors, Samarth Mehrotra, A. Perfors, 2019, CogSci.

Learning individual words and learning about words simultaneously

Joshua B. Tenenbaum, Fei Xu, Amy Perfors, 2011, CogSci.

Empiricism and Language Learnability

Nick Chater, Amy Perfors, Alexander Clark, 2015 .

Why are some word orders more common than others? A uniform information density account

Amy Perfors, Daniel J. Navarro, Luke Maurits, 2010, NIPS.

Simulated Evolution of Language: a Review of the Field

Amy Perfors, A. Perfors, 2002, J. Artif. Soc. Soc. Simul..

Modeling individual performance in cross-situational word learning

Amy Perfors, Yung Han Khoe, Andrew Hendrickson, 2019, CogSci.

Predicting human similarity judgments with distributional models: The value of word associations.

Amy Perfors, Daniel J. Navarro, Simon De Deyne, 2016, COLING.

The role of sampling assumptions in generalization with multiple categories

Amy Perfors, Daniel J. Navarro, Wai Keen Vong, 2013, CogSci.

To catch a liar: The effects of truthful and deceptive testimony on inferential learning

Patrick Shafto, Amy Perfors, Daniel J. Navarro, 2011, CogSci.

Constraining generalisation in artificial language learning : children are rational too

Amy Perfors, Elizabeth Wonnacott, E. Wonnacott, 2009 .

Memory limitations alone do not lead to over-regularization: An experimental and computational investigation

Amy Perfors, A. Perfors, 2011, CogSci.

Human decision making in black swan situations

Amy Perfors, Nicholas T. Van Dam, N. T. Dam, 2018, CogSci.

Bayesian modeling of sources of constraint in language acquisition

Amy Perfors, Elizabeth Wonnacott, E. Wonnacott, 2011 .

Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners

Danielle J. Navarro, Amy Perfors, Andrew T. Hendrickson, 2018, Cogn. Sci..

Enlightenment grows from fundamentals

Amy Perfors, Daniel J. Navarro, D. Navarro, 2011, Behavioral and Brain Sciences.

Sensitivity to communicative norms when deceiving without lying

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2015, CogSci.

Evidence for widespread thematic structure in the mental lexicon

Amy Perfors, Daniel J. Navarro, Steven Verheyen, 2015, CogSci.

Learnability in practice

Nick Chater, Amy Perfors, Alexander Clark, 2015 .

Anticipating changes: Adaptation and extrapolation in category learning

Amy Perfors, Daniel J. Navarro, 2012, CogSci.

Strong structure in weak semantic similarity: A graph based account

Amy Perfors, Daniel J. Navarro, Gerrit Storms, 2012, CogSci.

Why do echo chambers form? The role of trust, population heterogeneity, and objective truth

Danielle J. Navarro, Amy Perfors, D. Navarro, 2019, CogSci.

Supplemental materials for \Types, not tokens, are relevant for determining how far to generalize"

Amy Perfors, Keith Ransom, Daniel J. Navarro, 2011 .

Adult Regularization of Inconsistent Input Depends on Pragmatic Factors

Amy Perfors, A. Perfors, 2016 .

People are sensitive to hypothesis sparsity during category discrimination

Amy Perfors, Daniel J. Navarro, Andrew Hendrickson, 2014, CogSci.

Joint acquisition of word order and word reference

Amy Perfors, Luke Maurits, Daniel J. Navarro, 2009 .

When do learned transformations influence similarity and categorization?

Amy Perfors, Daniel J. Navarro, Andrew Hendrickson, 2017, CogSci.

The relevance of labels in semi-supervised learning depends on category structure

Amy Perfors, Daniel J. Navarro, Wai Keen Vong, 2014, CogSci.

Exploring the role that encoding and retrieval play in sampling effects

Amy Perfors, Keith Ransom, Keith Ransom, 2019, CogSci.

Inferring the hypothesis spaces underlying inductive generalization

Michael D. Lee, Amy Perfors, Daniel J. Navarro, 2014, CogSci.

Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One

Joshua B. Tenenbaum, Amy Perfors, Terry Regier, 2009, Cogn. Sci..

When Extremists Win: Cultural Transmission Via Iterated Learning When Populations Are Heterogeneous

Danielle J. Navarro, Amy Perfors, Scott D. Brown, 2018, Cogn. Sci..

Humans use different statistics for sequence analysis depending on the task

Amy Perfors, Daniel J. Navarro, Anna Ma-Wyatt, 2011, CogSci.

Higher order inference in verb argument structure acquisition

Joshua B. Tenenbaum, Amy Perfors, Elizabeth Wonnacott, 2008 .

Adaptive information source selection during hypothesis testing

Amy Perfors, Daniel J. Navarro, Andrew Hendrickson, 2014, CogSci.

Learning word meaning with little means: An investigation into the inferential capacity of paradigmatic information

Danielle J. Navarro, Amy Perfors, Simon De Deyne, 2018, CogSci.

Learning time-varying categories

Amy Perfors, Daniel J Navarro, Wai Keen Vong, 2013, Memory & cognition.

Sensitivity to hypothesis size during information search.

Amy Perfors, Daniel J. Navarro, Andrew T. Hendrickson, 2016 .

Running head : LEARNING OVERHYPOTHESES Learning overhypotheses with hierarchical Bayesian models

Joshua B. Tenenbaum, Amy Perfors, Charles Kemp, 2006 .

A cognitive analysis of deception without lying

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2017, CogSci.

Do additional features help or harm during category learning? An exploration of the curse of dimensionality in human learners

Amy Perfors, Daniel J. Navarro, Wai Keen Vong, 2016, CogSci.

Stronger evidence isn't always better: A role for social inference in evidence selection and interpretation

Patrick Shafto, Danielle J. Navarro, Amy Perfors, 2018, CogSci.

Computational approaches to induction

Nick Chater, Amy Perfors, Alexander Clark, 2015 .

Data Cleaning Script

Danielle J. Navarro, Brett K. Hayes, Amy Perfors, 2019 .

Distributional learning of syntax

Nick Chater, Amy Perfors, Alexander Clark, 2015 .

Infants can recognize words using partial phonetic information

Amy Perfors, Daniel Swingley, Anne Fernald, 1998 .

Representational and sampling assumptions drive individual differences in single category generalisation

Danielle J. Navarro, Amy Perfors, Keith Ransom, 2018, CogSci.

The impact of frequency on the evolution of category systems

Charles Kemp, Amy Perfors, Vanessa Ferdinand, 2019, CogSci.

People ignore token frequency when deciding how widely to generalize

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2014, CogSci.

REGULARIZATION OF LINGUISTIC VARIATION IN POPULATIONS

Amy Perfors, Kenny Smith, Elizabeth Wonnacott, 2012 .

Learnability, representation, and language: a bayesian approach

Amy Perfors, A. Perfors, 2008 .

What Bayesian modelling can tell us about statistical learning: What it requires and why it works

Amy Perfors, Daniel J. Navarro, D. Navarro, 2012 .

Learning Inductive Constraints: The Acquisition of Verb Argument Constructions

Amy Perfors, Josh Tenenbaum, Charles Kemp, 2007 .

What do our sampling assumptions affect: How we encode data or how we reason from it?

Brett K. Hayes, Amy Perfors, Keith Ransom, 2021, Journal of experimental psychology. Learning, memory, and cognition.

Social meta-inference and the evidentiary value of consensus

Amy Perfors, Keith Ransom, Rachel G. Stephens, 2021, CogSci.

Picking up speed in understanding: Speech processing efficiency and vocabulary growth across the 2nd year.

Amy Perfors, Anne Fernald, Virginia A Marchman, 2006, Developmental psychology.

Quantifying sentence acceptability measures : Reliability, bias, and variability

Amy Perfors, Andrew T. Hendrickson, Steven Langsford, 2018 .

Structure at every scale: A semantic network account of the similarities between unrelated concepts.

Amy Perfors, Daniel J Navarro, Gert Storms, 2016, Journal of experimental psychology. General.

Even arbitrary norms influence moral decision-making

Amy Perfors, Piers D. L. Howe, Campbell Pryor, 2018, Nature Human Behaviour.

When to walk away: The effect of variability on keeping options viable

Anastasia Ejova, Amy Perfors, Daniel J. Navarro, 2009 .

The Exploration Advantage: Children’s instinct to explore allows them to find information that adults miss.

Amy Perfors, Emily Sumner, Barbara Wiseheart Sarnecka, 2019 .

Cross-situational learning in a Zipfian environment

Amy Perfors, Andrew T. Hendrickson, Amy Perfors, 2019, Cognition.

Language learning, language use and the evolution of linguistic variation

Amy Perfors, Kenny Smith, Anna Samara, 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.

Bayesian Models of Cognition: What's Built in After All?

Amy Perfors, Amy Perfors, A. Perfors, 2012 .

70% of people surveyed said they’d download a coronavirus app.: Only 44% did. Why the gap?

Stephan Lewandowsky, Lewis Mitchell, Amy Perfors, 2020 .

Visual and Affective Grounding in Language and Mind

Amy Perfors, Guillem Collell, Simon De Deyne, 2018 .

Efficiency in understanding 1 Picking Up Speed in Understanding : Speech Processing Efficiency and Vocabulary Growth Across the Second Year

Amy Perfors, Anne Fernald, Virginia A. Marchman, 2004 .

Bayesian Models of Cognition Revisited: Setting Optimality Aside and Letting Data Drive Psychological Theory

Amy Perfors, Mark Steyvers, Daniel J Navarro, 2017, Psychological review.