Adam Sanborn

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 17

Top Topics

Continuous Space

Linear Functions

Sampling Strategies

Working Memory Capacity

Top Venues

PLoS Comput. Biol.

Publications

Lucas Castillo, Pablo León-Villagrá, Nick Chater, Adam Sanborn
Explaining the flaws in human random generation as local sampling with momentum. PLoS Comput. Biol. 20 (1) (2024)
Pablo León-Villagrá, Lucas Castillo, Nick Chater, Adam Sanborn
The Impact of Production Rates on Sequential Statistics and Distributional Properties in Random Generation. CogSci (2023)
Jian-Qiao Zhu, Adam Sanborn, Nick Chater, Tom Griffiths
Computation-Limited Bayesian Updating. CogSci (2023)
Pablo León-Villagrá, Lucas Castillo, Nick Chater, Adam Sanborn
Eliciting Human Beliefs using Random Generation. CogSci (2022)
Lucas Castillo, Pablo León-Villagrá, Nicholas Chater, Adam Sanborn
Local Sampling with Momentum Accounts for Human Random Sequence Generation. CogSci (2021)
Pablo León-Villagrá, Nicholas Chater, Adam Sanborn
Sampling Associations with (Un)related Suggestions. CogSci (2021)
Joakim Sundh, Jian-Qiao Zhu, Nicholas Chater, Adam Sanborn
How many instances come to mind when making probability estimates? CogSci (2020)
Jian-Qiao Zhu, Adam Sanborn, Nick Chater
Why Decisions Bias Perception: An Amortised Sequential Sampling Account. CogSci (2019)
Kevin Lloyd, Adam Sanborn, David Leslie, Stephan Lewandowsky
Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation. Cogn. Sci. 43 (12) (2019)
Jian-Qiao Zhu, Adam Sanborn, Nicholas Chater
Bayesian Inference Causes Incoherence in Human Probability Judgments. CogSci (2019)
Jake Spicer, Adam Sanborn, Ulrik R. Beierholm
Using Occam's razor and Bayesian modelling to compare discrete and continuous representations in numerostiy judgements. CogSci (2019)
Pablo León-Villagrá, Verena Klar, Adam Sanborn, Chris Lucas
Exploring the Representation of Linear Functions. CogSci (2019)
Jian-Qiao Zhu, Adam Sanborn, Nick Chater
Mental Sampling in Multimodal Representations. NeurIPS (2018)
Jake Spicer, Adam Sanborn
A Rational Approach to Stereotype Change. CogSci (2017)
Kevin Lloyd, Adam Sanborn, David Leslie, Stephan Lewandowsky
Why Does Higher Working Memory Capacity Help You Learn? CogSci (2017)
Alexandra Surdina, Adam Sanborn
Temporal variability in moral value judgement. CogSci (2017)
James Tripp, Adam Sanborn, Neil Stewart, Takao Noguchi
Choosing Poorly: Reward-Induced Strategy Shifts in Estimating the Probabilities of Conjunctions and Disjunctions. CogSci (2016)
James Tripp, Adam Sanborn, Neil Stewart, Takao Noguchi
Multiple Strategies in Conjunction and Disjunction Judgments: Most People are Normative Part of the Time. CogSci (2015)
Adam Sanborn, Takao Noguchi, James Tripp, Neil Stewart
Inference, Not Dilution in the Dilution Effect. CogSci (2015)
Marc Scholten, Daniel Read, Adam Sanborn
Time? Evaluation Rules in Intertemporal Choice. Cogn. Sci. 38 (3) (2014)
Takao Noguchi, Adam Sanborn, Neil Stewart
Non-parametric estimation of the individual's utility map. CogSci (2013)
Peter W. Battaglia, Tomer Ullman, Joshua B. Tenenbaum, Adam Sanborn, Kenneth D. Forbus, Tobias Gerstenberg, David A. Lagnado
Computational Models of Intuitive Physics. CogSci (2012)
Charles Blundell, Adam Sanborn, Thomas L. Griffiths
Look-Ahead Monte Carlo with People. CogSci (2012)
Jay B. Martin, Thomas L. Griffiths, Adam Sanborn
Testing the Efficiency of Markov Chain Monte Carlo With People Using Facial Affect Categories. Cogn. Sci. 36 (1) (2012)
Katherine A. Heller, Adam Sanborn, Nick Chater
Hierarchical Learning of Dimensional Biases in Human Categorization. NIPS (2009)
Adam Sanborn, Thomas L. Griffiths
Markov Chain Monte Carlo with People. NIPS (2007)