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Adam N. Sanborn - Publications

Affiliations: 
2010- Psychology University of Warwick, Coventry, England, United Kingdom 
Area:
Psychology
Website:
http://www2.warwick.ac.uk/fac/sci/psych/people/asanborn/
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25 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2021 Sanborn AN, Heller K, Austerweil JL, Chater N. REFRESH: A new approach to modeling dimensional biases in perceptual similarity and categorization. Psychological Review. PMID 34516151 DOI: 10.1037/rev0000310  0.645
2020 Spicer J, Sanborn AN, Beierholm UR. Using Occam's razor and Bayesian modelling to compare discrete and continuous representations in numerosity judgements. Cognitive Psychology. 122: 101309. PMID 32623183 DOI: 10.1016/j.cogpsych.2020.101309  0.396
2020 Zhu JQ, Sanborn AN, Chater N. The Bayesian sampler: Generic Bayesian inference causes incoherence in human probability judgments. Psychological Review. PMID 32191073 DOI: 10.1037/rev0000190  0.427
2019 Lloyd K, Sanborn A, Leslie D, Lewandowsky S. Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation. Cognitive Science. 43: e12805. PMID 31858632 DOI: 10.1111/Cogs.12805  0.355
2019 Spicer J, Sanborn AN. What does the mind learn? A comparison of human and machine learning representations. Current Opinion in Neurobiology. 55: 97-102. PMID 30870615 DOI: 10.1016/j.conb.2019.02.004  0.331
2019 Hsu AS, Martin JB, Sanborn AN, Griffiths TL. Identifying category representations for complex stimuli using discrete Markov chain Monte Carlo with people. Behavior Research Methods. PMID 30761464 DOI: 10.3758/S13428-019-01201-9  0.67
2017 Badham SP, Sanborn AN, Maylor EA. Deficits in category learning in older adults: Rule-based versus clustering accounts. Psychology and Aging. 32: 473-488. PMID 28816474 DOI: 10.1037/pag0000183  0.307
2016 Sanborn AN, Chater N. Bayesian Brains without Probabilities. Trends in Cognitive Sciences. 20: 883-893. PMID 28327290 DOI: 10.1016/j.tics.2016.10.003  0.324
2016 Sanborn AN, Beierholm UR. Fast and Accurate Learning When Making Discrete Numerical Estimates. Plos Computational Biology. 12: e1004859. PMID 27070155 DOI: 10.1371/journal.pcbi.1004859  0.396
2015 Sanborn AN. Types of approximation for probabilistic cognition: Sampling and variational. Brain and Cognition. PMID 26228974 DOI: 10.1016/j.bandc.2015.06.008  0.322
2015 Sanborn AN, Griffiths TL. Exploring the structure of mental representations by implementing computer algorithms with people Cognitive Modeling in Perception and Memory: a Festschrift For Richard M. Shiffrin. 212-228.  0.426
2014 Sanborn AN. Testing Bayesian and heuristic predictions of mass judgments of colliding objects. Frontiers in Psychology. 5: 938. PMID 25206345 DOI: 10.3389/fpsyg.2014.00938  0.365
2014 Sanborn AN, Hills TT. The frequentist implications of optional stopping on Bayesian hypothesis tests. Psychonomic Bulletin & Review. 21: 283-300. PMID 24101570 DOI: 10.3758/s13423-013-0518-9  0.315
2013 Sanborn AN, Mansinghka VK, Griffiths TL. Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychological Review. 120: 411-37. PMID 23458084 DOI: 10.1037/a0031912  0.538
2013 Sanborn AN, Silva R. Constraining bridges between levels of analysis: A computational justification for locally Bayesian learning Journal of Mathematical Psychology. 57: 94-106. DOI: 10.1016/J.Jmp.2013.05.002  0.343
2012 Martin JB, Griffiths TL, Sanborn AN. Testing the efficiency of Markov chain Monte Carlo with People using facial affect categories. Cognitive Science. 36: 150-62. PMID 21972923 DOI: 10.1111/J.1551-6709.2011.01204.X  0.596
2012 Griffiths TL, Vul E, Sanborn AN. Bridging Levels of Analysis for Probabilistic Models of Cognition Current Directions in Psychological Science. 21: 263-268. DOI: 10.1177/0963721412447619  0.52
2012 Griffiths TL, Sanborn AN, Canini KR, Navarro DJ. Categorization as nonparametric Bayesian density estimation The Probabilistic Mind: Prospects For Bayesian Cognitive Science. DOI: 10.1093/acprof:oso/9780199216093.003.0014  0.627
2011 Sanborn AN, Dayan P. Optimal decisions for contrast discrimination. Journal of Vision. 11. PMID 22159630 DOI: 10.1167/11.14.9  0.45
2010 Sanborn AN, Griffiths TL, Navarro DJ. Rational approximations to rational models: alternative algorithms for category learning. Psychological Review. 117: 1144-67. PMID 21038975 DOI: 10.1037/A0020511  0.552
2010 Shi L, Griffiths TL, Feldman NH, Sanborn AN. Exemplar models as a mechanism for performing Bayesian inference. Psychonomic Bulletin & Review. 17: 443-64. PMID 20702863 DOI: 10.3758/PBR.17.4.443  0.596
2010 Sanborn AN, Griffiths TL, Shiffrin RM. Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology. 60: 63-106. PMID 19703686 DOI: 10.1016/j.cogpsych.2009.07.001  0.672
2009 Sanborn AN, Griffiths TL. Markov chain Monte Carlo with people Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference.  0.441
2008 Cohen AL, Sanborn AN, Shiffrin RM. Model evaluation using grouped or individual data. Psychonomic Bulletin & Review. 15: 692-712. PMID 18792497 DOI: 10.3758/Pbr.15.4.692  0.582
2004 Sanborn AN, Malmberg KJ, Shiffrin RM. High-level effects of masking on perceptual identification. Vision Research. 44: 1427-36. PMID 15066401 DOI: 10.1016/J.Visres.2004.01.004  0.64
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