
The Library
Browse by Warwick Author
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Number of items: 53.
2021
Sanborn, Adam N., Zhu, J -Q., Spicer, Jake, Sundh, Joakim, León-Villagrá, Pablo and Chater, Nick (2021) Sampling as the human approximation to probabilistic inference. In: Muggleton, Stephen and Chater, Nicholas, (eds.) Human-Like Machine Intelligence. Oxford : Oxford University Press. ISBN 9780198862536 (In Press)
2020
Spicer, Jake, Sanborn, Adam N. and Beierholm, Ulrik R. (2020) Using Occam’s razor and Bayesian modelling to compare discrete and continuous representations in numerostiy judgements. Cognitive Psychology, 122 . 101309. doi:10.1016/j.cogpsych.2020.101309
Chater, Nick, Zhu, Jian-Qiao, Spicer, Jake, Sundh, Joakim, León-Villagrá, Pablo and Sanborn, Adam N. (2020) Probabilistic biases meet the Bayesian brain. Current Directions in Psychological Science, 29 (5). pp. 506-512. doi:10.1177/0963721420954801
Zhu, Jianqiao, Sanborn, Adam N. and Chater, Nick (2020) The Bayesian sampler : generic Bayesian inference causes incoherence in human probability. Psychological Review, 127 (5). pp. 719-748. doi:10.1037/rev0000190
Das-Friebel, Ahuti, Lenneis, Anita, Realo, Anu, Sanborn, Adam N., Tang, Nicole K. Y., Wolke, Dieter, von Mühlenen, Adrian and Lemola, Sakari (2020) Bedtime social media use, sleep, and affective wellbeing in young adults : an experience sampling study. Journal of Child Psychology and Psychiatry, 61 (10). pp. 1138-1149. doi:10.1111/jcpp.13326
Sanborn, Adam N., Noguchi, Takao, Tripp, James and Stewart, Neil (2020) A dilution effect without dilution : when missing evidence, not non-diagnostic evidence, is judged inaccurately. Cognition, 196 . 104110. doi:10.1016/j.cognition.2019.104110
Sanborn, Adam N., Zhu, Jianqiao, Spicer, Jake and Chater, Nick (2020) Sampling as a resource-rational constraint. Behavioral and Brain Sciences, 43 . e22. doi:10.1017/S0140525X19001584
2019
Lloyd, Kevin, Sanborn, Adam N., Leslie, David and Lewandowsky, Stephan (2019) Why higher working memory capacity may help you learn : sampling, search, and degrees of approximation. Cognitive Science, 43 (12). e12805. doi:10.1111/cogs.12805
Spicer, Jake and Sanborn, Adam N. (2019) What does the mind learn? A comparison of human and machine learning representations. Current Opinion in Neurobiology, 55 . pp. 97-102. doi:10.1016/j.conb.2019.02.004
Hsu, Anne S., Martin, Jay B., Sanborn, Adam N. and Griffiths, Thomas L. (2019) Identifying category representations for complex stimuli using discrete Markov chain Monte Carlo with people. Behavior Research Methods . pp. 1-11. doi:10.3758/s13428-019-01201-9
2018
Zhu , Jian-Qiao , Sanborn, Adam N. and Chater , Nick (2018) Mental sampling in multimodal representations. Advances in Neural Information Processing Systems (NIPS 2016) . 5753-5764 .
2017
Zhu, Jianqiao, Sanborn, Adam N. and Chater, Nick (2017) Mental sampling in multimodal representations. Working Paper. Coventry: University of Warwick. (Unpublished)
Badham, Stephen P., Sanborn, Adam N. and Maylor, Elizabeth A. (2017) Deficits in category learning in older adults : rule-based versus clustering accounts. Psychology and Aging, 32 (5). pp. 473-488. doi:10.1037/pag0000183
Ramlee, Fatanah, Sanborn, Adam N. and Tang, Nicole K. Y. (2017) What sways people's judgment of sleep quality? A quantitative choice-making study with good and poor sleepers. Sleep, 40 (7). zsx091. doi:10.1093/sleep/zsx091
Sanborn, Adam N. and Chater, Nick (2017) The sampling brain. Trends in Cognitive Sciences, 21 (7). pp. 492-493. doi:10.1016/j.tics.2017.04.009
Sanborn, Adam N., Tripp, James, Noguchi, Takao and Stewart, Neil (2017) Data for Combination Rules in Information Integration. [Dataset]
Surdina, Alexandra and Sanborn, Adam N. (2017) Temporal variability in moral value judgement. In: CogSci 2017 : 39th Annual Meeting of the Cognitive Science Society, London, UK, 26–29 Jul 2017. Published in: CogSci 2017 Proceedings of the 39th Annual Meeting of the Cognitive Science Society London, UK, 26-29 July 2017 pp. 3285-3290. ISBN 9780991196760 .
Lloyd, Kevin, Sanborn, Adam N., Leslie, David and Lewandowsky, Stephan (2017) Why does higher working memory capacity help you learn? In: CogSci 2017, London, 26-29 Jul 2017. Published in: CogSci 2017 Proceedings of the 39th Annual Meeting of the Cognitive Science Society London, UK, 26-29 July 2017 pp. 767-772. ISBN 9780991196760 .
Spicer, Jake and Sanborn, Adam N. (2017) A rational approach to stereotype change. In: CogSci 2017 : 39th Annual Meeting of the Cognitive Science Society, London, UK, 26–29 Jul 2017. Published in: CogSci 2017 Proceedings of the 39th Annual Meeting of the Cognitive Science Society London, UK, 26-29 July 2017 pp. 1102-1103. ISBN 9780991196760.
Sanborn, Adam N. (2017) Types of approximation for probabilistic cognition : sampling and variational. Brain and cognition, 112 . pp. 98-101. doi:10.1016/j.bandc.2015.06.008
2016
Sanborn, Adam N. and Chater, Nick (2016) Bayesian brains without probabilities. Trends in Cognitive Sciences, 20 (12). pp. 883-893. doi:10.1016/j.tics.2016.10.003
Scholten, Marc, Read, Daniel and Sanborn, Adam N. (2016) Cumulative weighing of time in intertemporal tradeoffs. Journal of Experimental Psychology: General, 145 (9). pp. 1177-1205. doi:10.1037/xge0000198
Sanborn, Adam N. and Beierholm, Ulrik R. (2016) Fast and accurate learning when making discrete numerical estimates. PLoS Computational Biology, 12 (4). e1004859. doi:10.1371/journal.pcbi.1004859
2015
Sanborn, Adam N. (2015) Bayesian models of cognition. In: Jaeger, Dieter and Jung, Ranu, (eds.) Encyclopedia of Computational Neuroscience. Springer, pp. 624-625. ISBN 9781461466758
Sanborn, Adam N. and Griffiths, Thomas L. (2015) Exploring the structure of mental representations by implementing computer algorithms with people. In: Raaijmakers, J. G. W. and Criss, A. H. and Goldstone, R. L. and Nosofsky, R. M. and Steyvers, M., (eds.) Cognitive Modeling in Perception and Memory: A Festschrift for Richard M. Shiffrin. New York: Psychology Press ; Taylor & Francis Group, pp. 212-228.
Tripp, James, Sanborn, Adam N., Stewart, Neil and Noguchi, Takao (2015) Multiple strategies in conjunction and disjunction judgments : most people are normative part of the time. In: CogSci 2015 : 37th annual conference of the Cognitive Science Society, Pasadena, California, 22-25 Jul 2015. Published in: Proceedings of the 37th Annual Meeting of the Cognitive Science Society. Austin, TX ISBN 9780991196722.
2014
Sanborn, Adam N. (2014) Testing Bayesian and heuristic predictions of mass judgments of colliding objects. Frontiers in Psychology, Volume 5 . Article number 938. doi:10.3389/fpsyg.2014.00938
Scholten, Marc, Read, Daniel and Sanborn, Adam N. (2014) Weighing outcomes by time or against time? Evaluation rules in intertemporal choice. Cognitive Science, 38 (3). pp. 399-438. doi:10.1111/cogs.12104
Sanborn, Adam N. and Hills, Thomas Trenholm (2014) The frequentist implications of optional stopping on Bayesian hypothesis tests. Psychonomic Bulletin & Review , Volume 21 (Number 2). pp. 283-300. doi:10.3758/s13423-013-0518-9
Tang, Nicole K. Y. and Sanborn, Adam N. (2014) Better quality sleep promotes daytime physical activity in patients with chronic pain? : A multilevel analysis of the within-person relationship. PLoS One, Volume 9 (Number 3). pp. 1-9. Article number e92158. doi:10.1371/journal.pone.0092158
Sanborn, Adam N., Hills, Thomas Trenholm, Dougherty, Michael R., Thomas, Rick P., Yu, Erica C. and Sprenger, Amber M. (2014) Reply to Rouder (2014) : good frequentist properties raise confidence. Psychonomic Bulletin & Review , Volume 21 (Number 2). pp. 309-311. doi:10.3758/s13423-014-0607-4
2013
Sanborn, Adam N., Mansinghka, Vikash K. and Griffiths, Thomas L. (2013) Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychological Review, 120 (2). pp. 411-437. doi:10.1037/a0031912
Sanborn, Adam N. and Silva, Ricardo (2013) Constraining bridges between levels of analysis : a computational justification for locally Bayesian learning. Journal of Mathematical Psychology, Volume 57 (Number 3-4). pp. 94-106. doi:10.1016/j.jmp.2013.05.002
Noguchi, Takao, Sanborn, Adam N. and Stewart, Neil (2013) Non-parametric estimation of the individual's utility map. In: COGSCI 2013 : Thirty-fifth annual conference of the Cognitive Science Society, Berlin, Germany, 31 Jul - 3 Aug 2013. Published in: Proceedings of the Thirty-Fifth Annual Conference of the Cognitive Science Society pp. 3145-3150. ISBN 9780976831891.
2012
Griffiths, T. L., Vul, E. and Sanborn, Adam N. (2012) Bridging levels of analysis for probabilistic models of cognition. Current Directions in Psychological Science, Volume 21 (Number 4). pp. 263-268. doi:10.1177/0963721412447619
Tang, Nicole K. Y., Goodchild, Claire E., Sanborn, Adam N., Howard, Jonathan and Salkovskis, Paul M. (2012) Deciphering the temporal link between pain and sleep in a heterogeneous chronic pain patient sample : a multilevel daily process study. Sleep, Vol.35 (No.5). pp. 675-687. doi:10.5665/sleep.1830
Martin, J. B., Griffiths, Thomas L. and Sanborn, Adam N. (2012) Testing the efficiency of Markov Chain Monte Carlo with people using facial affect categories. Cognitive Science, 36 (11). pp. 150-162. doi:10.1111/j.1551-6709.2011.01204.x
2011
Griffiths, Thomas L., Sanborn, Adam N., Canini, Kevin R., Navarro, Daniel J. and Tenenbaum, Joshua B. (2011) Nonparametric Bayesian models of categorization. In: Pothos, Emmanuel M. and Wills, Andy J. , (eds.) Formal Approaches in Categorization. Cambridge: Cambridge University Press, pp. 173-198. ISBN 9780521190480
Sanborn, Adam N. and Dayan, P. (2011) Optimal decisions for contrast discrimination. Journal of Vision, Vol.11 (No.14). Article no. 9. doi:10.1167/11.14.9
2010
Shi, Lei, Griffiths, Thomas L., Feldman, Naomi H. and Sanborn, Adam N. (2010) Exemplar models as a mechanism for performing Bayesian inference. Psychonomic bulletin & review, Vol.17 (No.4). pp. 443-64. doi:10.3758/PBR.17.4.443
Sanborn, Adam N., Griffiths, Thomas L. and Navarro, Daniel J (2010) Rational approximations to rational models : alternative algorithms for category learning. Psychological Review, Vol.117 (No.4). pp. 1144-67. doi:10.1037/a0020511
Sanborn, Adam N., Griffiths, Thomas L. and Shiffrin, Richard M. (2010) Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology, Vol.60 (No.2). pp. 63-106. doi:10.1016/j.cogpsych.2009.07.001
2009
Sanborn, Adam N., Mansinghka, Vikash and Griffiths , Thomas L. (2009) A Bayesian framework for modeling intuitive dynamics. In: CogSci 2009: 31st Annual Meeting of the Cognitive Science Society, Amsterdam, Netherlands, 29 Jul - 1 Aug 2009
Sanborn, Adam N. and Silva, Ricardo (2009) Belief propagation and locally Bayesian learning. In: CogSci 2009: 31st Annual Meeting of the Cognitive Science Society, Amsterdam, Netherlands, 29 Jul - 1 Aug 2009. Published in: Proceedings of the 31st Annual Conference of the Cognitive Science Society
Heller, Katherine, Sanborn, Adam N. and Chater, Nick (2009) Hierarchical learning of dimensional biases in human categorization. In: Lafferty , J. Clayton (James Clayton), 1928- and Williams , C., (eds.) Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009, December 7-10, 2009, Vancouver, B.C., Canada. La Jolla, C.A.: Neural Information Processing Systems. ISBN 9781615679119
Griffiths, Thomas L., Canini, Kevin R., Sanborn, Adam N. and Navarro, Daniel J. (2009) Unifying rational models of categorization via the hierarchical Dirichlet process. In: Proceedings of the 29th Annual Conference of the Cognitive Science Society. Mahwah, N.J.: Lawrence Erlbaum, p. 323. ISBN 9781605605074
Martin, Jason, Griffiths , Thomas L. and Sanborn, Adam N. (2009) A walk through face space : affect classification using Markov chain Monte Carlo. In: CogSci 2009: 31st Annual Meeting of the Cognitive Science Society, Amsterdam, Netherlands, 29 Jul - 1 Aug 2009
2008
Griffiths, Thomas L., Sanborn, Adam N., Canini, Kevin R. and Navarro, Daniel J. (2008) Categorization as nonparametric Bayesian density estimation. In: Chater, Nick and Oaksford, Mike, (eds.) The probabilistic mind : prospects for Bayesian cognitive science. Oxford : Oxford University Press, pp. 303-328. ISBN 9780199216093
Sanborn, Adam N. and Griffiths, Thomas L. (2008) Markov chain Monte Carlo with people. In: Platt, John C., (ed.) Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007. Red Hook, N.Y.: Curran Associates Inc, pp. 1265-1272. ISBN 9781605603520
Cohen, Andrew L., Sanborn, Adam N. and Shiffrin, Richard M. (2008) Model evaluation using grouped or individual data. Psychonomic Bulletin & Review, Vol.15 (No.4). pp. 692-712. doi:10.3758/PBR.15.4.692
2006
Sanborn, Adam N., Griffiths, Thomas L. and Navarro, Daniel J. (2006) A more rational model of categorization. In: Proceedings of the 28th annual conference of the Cognitive Science Society. Mahwah, N.J.: Lawrence Erlbaum, pp. 726-731. ISBN 9780976831822
2004
Sanborn, Adam N., Malmberg, Kenneth J. and Shiffrin, Richard M. (2004) High-level effects of masking on perceptual identification. Vision Research, Vol.44 (No.12). pp. 1427-1436. doi:10.1016/j.visres.2004.01.004
2003
Morrow, Daniel G., Ridolfo, Heather E., Menard, William E., Sanborn, Adam N., Stine-Morrow, Elizabeth A. L., Magnor, Cliff, Herman, Larry, Teller, Thomas and Bryant, David (2003) Environmental support promotes expertise-based mitigation of age differences on pilot communication tasks. Psychology and Aging, Vol.18 (No.2). pp. 268-284. doi:10.1037/0882-7974.18.2.268
This list was generated on Sun Apr 11 10:33:22 2021 BST.