Adam Sanborn

According to our database, Adam Sanborn authored at least 28 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Explaining the flaws in human random generation as local sampling with momentum.

Lucas Castillo, Pablo León-Villagrá, Nick Chater, Adam Sanborn

PLoS Comput. Biol., January, 2024

2022

Understanding the structure of cognitive noise.

Jian-Qiao Zhu, Pablo León-Villagrá, Nick Chater, Adam N. Sanborn

PLoS Comput. Biol., 2022

Sampling as the Human Approximation to Probabilistic Inference.

Adam Sanborn, Jian-Qiao Zhu, Jake Spicer, Joakim Sundh, Pablo León-Villagrá, Nick Chater

Proceedings of the Human-Like Machine Intelligence., 2022

2021

Sampling Associations with (Un)related Suggestions.

Pablo León-Villagrá, Nicholas Chater, Adam Sanborn

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

Local Sampling with Momentum Accounts for Human Random Sequence Generation.

Lucas Castillo, Pablo León-Villagrá, Nicholas Chater, Adam Sanborn

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

2020

How many instances come to mind when making probability estimates?

Joakim Sundh, Jian-Qiao Zhu, Nicholas Chater, Adam Sanborn

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019

Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation.

Kevin Lloyd, Adam Sanborn, David S. Leslie, Stephan Lewandowsky

Cogn. Sci., 2019

Bayesian Inference Causes Incoherence in Human Probability Judgments.

Jian-Qiao Zhu, Adam Sanborn, Nicholas Chater

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Why Decisions Bias Perception: An Amortised Sequential Sampling Account.

Jian-Qiao Zhu, Adam Sanborn, Nick Chater

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Using Occam's razor and Bayesian modelling to compare discrete and continuous representations in numerostiy judgements.

Jake Spicer, Adam Sanborn, Ulrik R. Beierholm

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Exploring the Representation of Linear Functions.

Pablo León-Villagrá, Verena Klar, Adam Sanborn, Chris Lucas

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018

Mental Sampling in Multimodal Representations.

Jian-Qiao Zhu, Adam Sanborn, Nick Chater

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Temporal variability in moral value judgement.

Alexandra Surdina, Adam Sanborn

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

A Rational Approach to Stereotype Change.

Jake Spicer, Adam Sanborn

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Why Does Higher Working Memory Capacity Help You Learn?

Kevin Lloyd, Adam Sanborn, David S. Leslie, Stephan Lewandowsky

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016

Fast and Accurate Learning When Making Discrete Numerical Estimates.

Adam N. Sanborn, Ulrik R. Beierholm

PLoS Comput. Biol., 2016

Choosing Poorly: Reward-Induced Strategy Shifts in Estimating the Probabilities of Conjunctions and Disjunctions.

James Tripp, Adam Sanborn, Neil Stewart, Takao Noguchi

Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2015

Multiple Strategies in Conjunction and Disjunction Judgments: Most People are Normative Part of the Time.

James Tripp, Adam Sanborn, Neil Stewart, Takao Noguchi

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

Inference, Not Dilution in the Dilution Effect.

Adam Sanborn, Takao Noguchi, James Tripp, Neil Stewart

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2014

Cognition, Bayesian Models of.

Adam N. Sanborn

Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Weighing Outcomes <i>by</i> Time or <i>Against</i> Time? Evaluation Rules in Intertemporal Choice.

Marc Scholten, Daniel Read, Adam Sanborn

Cogn. Sci., 2014

2013

Non-parametric estimation of the individual's utility map.

Takao Noguchi, Adam Sanborn, Neil Stewart

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012

Testing the Efficiency of Markov Chain Monte Carlo With People Using Facial Affect Categories.

Jay B. Martin, Thomas L. Griffiths, Adam Sanborn

Cogn. Sci., 2012

Identifying representations of categories of discrete items using Markov chain Monte Carlo with People.

Anne S. Hsu, Jay B. Martin, Adam N. Sanborn, Thomas L. Griffiths

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

Look-Ahead Monte Carlo with People.

Charles Blundell, Adam Sanborn, Thomas L. Griffiths

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

Computational Models of Intuitive Physics.

Peter W. Battaglia, Tomer D. Ullman, Joshua B. Tenenbaum, Adam Sanborn, Kenneth D. Forbus, Tobias Gerstenberg, David A. Lagnado

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2009

Hierarchical Learning of Dimensional Biases in Human Categorization.

Katherine A. Heller, Adam Sanborn, Nick Chater

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007

Markov Chain Monte Carlo with People.

Adam Sanborn, Thomas L. Griffiths

Proceedings of the Advances in Neural Information Processing Systems 20, 2007