Charles Kemp

发表

Discovering hidden causes using statistical evidence

Christopher G. Lucas, Charles Kemp, Kenneth Holstein, 2014, CogSci.

Theory-based Bayesian models of inductive learning and reasoning

J. Tenenbaum, T. Griffiths, Charles Kemp, 2006, Trends in Cognitive Sciences.

Probabilistic models of cognition: exploring representations and inductive biases

J. Tenenbaum, T. Griffiths, Charles Kemp, 2010, Trends in Cognitive Sciences.

A unified theory of counterfactual reasoning

Christopher G. Lucas, Charles Kemp, Charles Kemp, 2012, CogSci.

An integrated account of generalization across objects and features

J. Tenenbaum, Charles Kemp, Patrick Shafto, 2012, Cognitive Psychology.

Superspace extrapolation reveals inductive biases in function learning

Christopher G. Lucas, Charles Kemp, Douglas Sterling, 2012, CogSci.

Evaluating the inverse decision-making approach to preference learning

Christopher G. Lucas, Charles Kemp, Alan Jern, 2011, NIPS.

A probabilistic model of theory formation

J. Tenenbaum, T. Griffiths, Charles Kemp, 2010, Cognition.

Learning Cross-cutting Systems of Categories

Vikash K. Mansinghka, J. Tenenbaum, Charles Kemp, 2006 .

A probabilistic account of exemplar and category generation

Charles Kemp, Alan Jern, 2013, Cognitive Psychology.

Bayesian Special Section Learning Overhypotheses with Hierarchical Bayesian Models

J. Tenenbaum, Charles Kemp, Amy Perfors, 2022 .

One-Shot Learning with Bayesian Networks

Andrew L. Maas, Charles Kemp, 2009 .

Semi-Supervised Learning with Trees

Thomas L. Griffiths, Joshua B. Tenenbaum, Charles Kemp, 2003, NIPS.

A decision network account of reasoning about other people’s choices

Charles Kemp, Alan Jern, 2015, Cognition.

Theory Acquisition and the Language of Thought

Noah D. Goodman, J. Tenenbaum, Charles Kemp, 2008 .

Learning Systems of Concepts with an Infinite Relational Model

Thomas L. Griffiths, Naonori Ueda, Joshua B. Tenenbaum, 2006, AAAI.

Bayesian Models of Inductive Learning

Thomas L. Griffiths, Joshua B. Tenenbaum, Charles Kemp, 2006 .

Learning Domain Structures

J. Tenenbaum, Charles Kemp, Amy Perfors, 2004 .

Belief polarization is not always irrational.

Charles Kemp, Alan Jern, K. Chang, 2014, Psychological review.

Discovering Latent Classes in Relational Data

Thomas L. Griffiths, Joshua B. Tenenbaum, Charles Kemp, 2004 .

Structured statistical models of inductive reasoning.

J. Tenenbaum, Charles Kemp, 2009, Psychological review.

How to Grow a Mind: Statistics, Structure, and Abstraction

Charles Kemp, Noah D. Goodman, Joshua B Tenenbaum, 2011, Science.

What if? Counterfactual reasoning, pretense, and the role of possible worlds

Alison Gopnik, Nick Chater, Daphna Buchsbaum, 2013, CogSci.

Learning Causal Schemata

Noah D. Goodman, J. Tenenbaum, Charles Kemp, 2007 .

Title : The imaginary fundamentalists : The unshocking truth about Bayesian cognitive science

Noah D. Goodman, J. Tenenbaum, T. Griffiths, 2011 .

First Workshop on Computational Neurolinguistics Learning Semantic Features for Fmri Data from Definitional Text Concept Classification with Bayesian Multi-task Learning Wordnet Based Features for Predicting Brain Activity Associated with Meanings of Nouns an Investigation on Polysemy and Lexical Or

Bradford Z. Mahon, Nathaniel J. Smith, Ben D. Amsel, 2010 .

A taxonomy of inductive problems

Charles Kemp, Alan Jern, 2013, Psychonomic Bulletin & Review.

BAYESIAN SPECIAL SECTION Learning overhypotheses with hierarchical Bayesian models

J. Tenenbaum, Charles Kemp, Amy Perfors, 2007 .

Modeling the Acquisition of Domain Structure and Feature Understanding

J. Tenenbaum, Charles Kemp, Amy Perfors, 2005 .

People learn other people’s preferences through inverse decision-making

Christopher G. Lucas, Charles Kemp, Alan Jern, 2017, Cognition.

Evaluating the inverse reasoning account of object discovery

Charles Kemp, C. Carroll, 2015, Cognition.

Successful structure learning from observational data

Charles Kemp, Ralf Mayrhofer, B. Deverett, 2018, Cognition.

An improved probabilistic account of counterfactual reasoning.

Christopher G. Lucas, Charles Kemp, 2015, Psychological review.

Medial Axis Representations for the Analysis of Human Shape in Images

Charles Kemp, 2000 .

Proceedings of the 36th Annual Conference of the Cognitive Science Society

Christopher G. Lucas, Kenneth Holstein, Charles Kemp, 2014 .

Category and feature identification.

Charles Kemp, Luigi Lombardi, Charles Kemp, 2010, Acta psychologica.

Inductive reasoning about causally transmitted properties

Joshua B. Tenenbaum, Charles Kemp, Patrick Shafto, 2008, Cognition.

Inductive Reasoning: Theory-Based Bayesian Models of Inductive Reasoning

Joshua B. Tenenbaum, Charles Kemp, Patrick Shafto, 2007 .

An efficient communication analysis of morpho-syntactic grammatical features

Charles Kemp, Francis Mollica, 2020, CogSci.

Running head : THEORY FORMATION A probabilistic model of theory formation

Charles Kemp, 2009 .

Chaining and the growth of linguistic categories

Charles Kemp, Yang Xu, Amir Ahmad Habibi, 2020, Cognition.

Chaining and the growth of linguistic categories

Charles Kemp, Yang Xu, Amir Ahmad Habibi, 2020, Cognition.

Learning Overhypotheses

J. Tenenbaum, Charles Kemp, Amy Perfors, 2006 .

Practical Challenges for Developmental Robotics

Charles Kemp, W. Coulter, 2022 .

Nonsense and Sensibility: Inferring Unseen Possibilities

J. Tenenbaum, Charles Kemp, Lauren A. Schmidt, 2006 .

Information-theoretic efficiency and semantic variation: The case of color naming

Charles Kemp, Naftali Tishby, Terry Regier, 2018, Annual Meeting of the Cognitive Science Society.

Author ' s personal copy Inductive reasoning about causally transmitted properties q

J. Tenenbaum, Charles Kemp, Patrick Shafto, 1997 .

Communicative need and color naming

Charles Kemp, Naftali Tishby, Terry Regier, 2019, CogSci.

Communicative need in colour naming

Naftali Tishby, Charles Kemp, Noga Zaslavsky, 2020, Cognitive neuropsychology.

Word formation supports efﬁcient communication: The case of compounds

Charles Kemp, Yang Xu, Lea Frermann, 2022 .

Inferring other people's relationships by observing their social interactions

Charles Kemp, Anna Scott, Alan Jern, 2018, CogSci.

The impact of frequency on the evolution of category systems

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

Simplification Is Not Dominant in the Evolution of Chinese Characters

Charles Kemp, James Winters, Piers Kelly, 2022, Open Mind.

Structured Priors for Structure Learning

Vikash K. Mansinghka, J. Tenenbaum, T. Griffiths, 2006, UAI.

Nonsense and Sensibility: Inferring Unseen Possibilities

J. Tenenbaum, Charles Kemp, Lauren A. Schmidt, 2006 .

Learning and using relational theories : supporting material

Noah D. Goodman, J. Tenenbaum, Charles Kemp, 2007 .

A taxonomy of inductive problems

Charles Kemp, Alan Jern, 2013, Psychonomic Bulletin & Review.

Efficient compression in color naming and its evolution

Charles Kemp, Naftali Tishby, Terry Regier, 2018, Proceedings of the National Academy of Sciences.

Languages Support Efficient Communication about the Environment: Words for Snow Revisited

Charles Kemp, Terry Regier, Alexandra Carstensen, 2016, PloS one.

The forms and meanings of grammatical markers support efficient communication

Charles Kemp, T. Regier, Yang Xu, 2021, Proceedings of the National Academy of Sciences.

Semantic Typology and Efficient Communication

Yang Xu, Terry Regier, Charles Kemp, 2018 .

Word Meanings across Languages Support Efficient Communication

Terry Regier, Paul Kay, Charles Kemp, 2015 .

Kinship Categories Across Languages Reflect General Communicative Principles

Charles Kemp, Terry Regier, Charles Kemp, 2012, Science.

Learning to Learn Causal Models

Joshua B. Tenenbaum, Charles Kemp, Noah D. Goodman, 2010, Cogn. Sci..

A probabilistic model of cross-categorization

Joshua B. Tenenbaum, Charles Kemp, Vikash K. Mansinghka, 2011, Cognition.

Exploring the conceptual universe.

Charles Kemp, Charles Kemp, 2012, Psychological review.

The discovery of structural form

Charles Kemp, Joshua B Tenenbaum, J. Tenenbaum, 2008, Proceedings of the National Academy of Sciences.

Bayesian models of cognition

Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum, 2008 .

The acquisition of inductive constraints

Joshua B. Tenenbaum, Charles Kemp, J. Tenenbaum, 2008 .

Long-Term Learning for Web Search Engines

Kotagiri Ramamohanarao, Charles Kemp, Charles Kemp, 2002, PKDD.

Perceptual Grouping Explains Similarities in Constellations Across Cultures

Daniel R. Little, Charles Kemp, S. Cropper, 2020, Psychological science.

Decision factors that support preference learning

Charles Kemp, Alan Jern, Charles Kemp, 2011, CogSci.

Learning Overhypotheses

J. Tenenbaum, Charles Kemp, A. Perfors, 2006 .

Object discovery and identification

Alan Jern, Charles Kemp, Fei Xu, 2009, NIPS 2009.

Quantification and the language of thought

Charles Kemp, Charles Kemp, 2009, NIPS.

None of the Above: A Bayesian Account of the Detection of Novel Categories

Charles Kemp, Daniel J Navarro, Charles Kemp, 2017, Psychological review.

Running head : LEARNING OVERHYPOTHESES Learning overhypotheses with hierarchical Bayesian models

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

Evolution and efficiency in color naming: The case of Nafaanra

Charles Kemp, Naftali Tishby, Terry Regier, 2019, CogSci.

The evolution of color naming reflects pressure for efficiency: Evidence from the recent past

Naftali Tishby, Charles Kemp, T. Regier, 2021, bioRxiv.

Inference and communication in the game of Password

Yang Xu, Charles Kemp, Charles Kemp, 2010, NIPS.

Color naming reflects both perceptual structure and communicative need

Charles Kemp, Naftali Tishby, Terry Regier, 2018, Top. Cogn. Sci..

Modeling Semantic Cognition as Logical Dimensionality Reduction

Yarden Katz, Kristian Kersting, Joshua B. Tenenbaum, 2008 .

Learning and using relational theories

Joshua B. Tenenbaum, Charles Kemp, Noah D. Goodman, 2007, NIPS.

Kinship Categories across Languages Reflect General

Charles Kemp, Terry Regier, Charles Kemp, 2012 .

Learning Deterministic Causal Networks from Observational Data

Ben Deverett, Charles Kemp, Charles Kemp, 2012, CogSci.

Arengiya Anyainya Aidmeniya Aburliya Adardiya Agngiya Aweniya Amaidya Abmarliya Awaadya Anguriya Adiaya Angeliya Algyeliya Adniadya Aleriya Umbaidya Anowadya Muriya Angenduriya Amburniya Andungiya Aneriya Aiyenga Undyaidya Gnaldena

J. Tenenbaum, T. Griffiths, Charles Kemp, 2004 .

Structured models of semantic cognition

Joshua B. Tenenbaum, Charles Kemp, J. Tenenbaum, 2008, Behavioral and Brain Sciences.

Concept Learning and Modal Reasoning

Charles Kemp, Alan Jern, Faye Han, 2011, CogSci.

“Structured statistical models of inductive reasoning”: Correction.

J. Tenenbaum, Charles Kemp, 2009 .

Capturing mental state reasoning with influence diagrams

Charles Kemp, Alan Jern, Charles Kemp, 2011, CogSci.

A toolbox of methods for probabilistic inference

Charles Kemp, Caleb Eddy, Charles Kemp, 2017, CogSci.

Inductive reasoning in humans and large language models

Charles Kemp, Keith Ransom, Andrew Perfors, 2023, Cognitive Systems Research.

Theory-Based Induction

Joshua B. Tenenbaum, Charles Kemp, J. Tenenbaum, 2003 .

Predicting strategy choice in word formation: A case study of reuse and compounding

Charles Kemp, Yang Xu, Lea Frermann, 2023 .

Learning annotated hierarchies from relational data

Joshua B. Tenenbaum, Charles Kemp, Daniel M. Roy, 2006, NIPS.

Inductive reasoning about chimeric creatures

Charles Kemp, Charles Kemp, 2011, NIPS.

Abstraction and Relational learning

Charles Kemp, Alan Jern, Charles Kemp, 2009, NIPS.

Quantifying informativeness of names in visual space

Charles Kemp, Yang Xu, Gemma Boleda, 2023 .

Combining causal and similarity-based reasoning

Joshua B. Tenenbaum, Charles Kemp, Patrick Shafto, 2006, NIPS.

Semantic categories of artifacts and animals reflect efficient coding pdf

Naftali Tishby, Terry Regier, Noga Zaslavsky, 2019, SCIL.

Reasoning about social choices and social relationships

Charles Kemp, Alan Jern, Charles Kemp, 2014, CogSci.

Efficient human-like semantic representations via the Information Bottleneck principle pdf

Charles Kemp, Naftali Tishby, Terry Regier, 2018, ArXiv.

Goal Recognition with Timing Information

Charles Kemp, N. Lipovetzky, Chenyuan Zhang, 2023, ICAPS.

Kinship Categories Across Languages Reflect General Communicative Principles

Charles Kemp, T. Regier, 2012, Science.

The discovery of structural form

J. Tenenbaum, Charles Kemp, 2008, Proceedings of the National Academy of Sciences.

Learning overhypotheses with hierarchical Bayesian models.

J. Tenenbaum, Charles Kemp, A. Perfors, 2007, Developmental science.

Category and feature identification.

Charles Kemp, K. Chang, L. Lombardi, 2010, Acta psychologica.

Structured Priors for Structure Learning

Shan Gao, Zhi Geng, Vikash K. Mansinghka, 2006, UAI.

Learning to Learn Causal Models

Noah D. Goodman, J. Tenenbaum, Charles Kemp, 2010, Cogn. Sci..

Probabilistic models of cognition: exploring representations and inductive biases

J. Tenenbaum, T. Griffiths, Charles Kemp, 2010, Trends in Cognitive Sciences.

Evaluating the inverse reasoning account of object discovery

Charles Kemp, C. Carroll, 2015, Cognition.

Successful structure learning from observational data

Charles Kemp, Ralf Mayrhofer, B. Deverett, 2018, Cognition.

An improved probabilistic account of counterfactual reasoning.

Christopher G. Lucas, Charles Kemp, 2015, Psychological review.

A Computational Evaluation of Two Laws of Semantic Change

Yang Xu, Charles Kemp, Charles Kemp, 2015, CogSci.

A Generative Theory of Similarity

Joshua B. Tenenbaum, Charles Kemp, J. Tenenbaum, 2005 .