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Adam Sanborn Research Profile

Job Title
Professor
Department
Psychology
Phone
(024) 761 51354
Web Link
Research Interests

Explaining human categorisation and perception as rational behaviour. Examining how people use approximate solutions in difficult cognitive tasks. Methods for data collection and analysis.

Biography

Adam Sanborn is a Professor of Psychology at the University of Warwick. He gained his PhD in Psychological & Brain Sciences and Cognitive Science at Indiana University, and did his postdoctoral work at the Gatsby Computational Neuroscience Unit at UCL. Adam is interested in the rationality of human behaviour, which he studies with Bayesian models, approximations to Bayesian models, and behavioural experiments. His research has been published in leading psychology journals such as Psychological Review, Trends in Cognitive Sciences, and Cognitive Psychology, and he has won best paper awards in both psychology and computer science. His work has been funded by the ESRC, ERC, Alan Turing Institute, and NIESR, and he serves as Associate Editor for the Journal of Experimental Psychology: Learning, Memory, and Cognition.

Representative Publications:

Sanborn, A.N., Heller, K., Austerweil, J.L., & Chater, N. (2021). REFRESH: A new approach to modeling dimensional biases in perceptual similarity and categorization. Psychological Review, 128(6), 1145-1186.

Sanborn, A.N. & Chater, N. (2016). Bayesian brains without probabilities. Trends in Cognitive Sciences, 20(12), 883-893.

Sanborn, A. N., Mansinghka, V. K., & Griffiths, T. L. (2013). Reconciling intuitive physics and Newtonian mechanics for colliding objects. Psychological Review, 120, 411-437.

Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2010). Rational approximations to rational models: Alternative algorithms for category learning. Psychological Review, 117, 1144-1167.

  • Gri?iths, T. L., Sanborn, Adam N., 2024. Approximate probabilistic inference. Griffiths, T. L.; Chater, Nick; Tenenbaum, Joshua B. (eds.), Bayesian models of cognition : reverse engineering the mind, Boston, MA, MIT Press
  • Smith, K. A., Hamrick, J. B., Sanborn, Adam N., Battaglia, P. W., Gerstenberg, T., Ullman, T. D., Tenenbaum, J. B., 2024. Intuitive physics as probabilistic inference. Griffiths, T. L.; Chater, Nick; Tenenbaum, Joshua B. (eds.), Bayesian models of cognition : reverse engineering the mind, Boston, MA, MIT Press
  • Austerwell, J., Sanborn, Adam N., Lucas, C., Griffiths, T. L., 2024. Capturing the growth of knowledge with nonparametric Bayesian models. Griffiths, T. L.; Chater, Nick; Tenenbaum, Joshua B. (eds.), Bayesian models of cognition : reverse engineering the mind, Boston, MA, MIT Press
  • Griffiths, T. L., Vul, E., Sanborn, Adam N., Chater, Nick, 2024. Sampling as a bridge across levels of analysis. Griffiths, T. L.; Chater, Nick; Tenenbaum, Joshua B. (eds.), Bayesian models of cognition : reverse engineering the mind, Boston, MA, MIT Press
  • Griffiths, T. L., Sanborn, Adam N., Marjieh, R., Langlois, T., Xu, J., Jacoby, N., 2024. Estimating subjective probability distributions. Griffiths, T. L.; Chater, Nick; Tenenbaum, Joshua B. (eds.), Bayesian models of cognition : reverse engineering the mind, Boston, MA, MIT Press
  • Sundh, Joakim, Sanborn, Adam N., Zhu, Jian-Qiao, Spicer, Jake, León-Villagrá, Pablo, Chater, Nick, 2023. Approximating Bayesian inference through internal sampling. In Fiedler, Klaus; Juslin, Peter; Denrell, Jerker (eds.), Sampling in Judgment and Decision Making, Cambridge, United Kingdom, Cambridge University Press, pp. 490-512
  • Zhu, Jian-Qiao, Chater, Nick, León-Villagrá, Pablo, Spicer, Jake, Sundh, Joakim, Sanborn, Adam N., 2023. An introduction to psychologically plausible sampling schemes for approximating Bayesian inference. In Fiedler, Klaus; Juslin, Peter; Denrell, Jerker (eds.), Sampling in Judgment and Decision Making, Cambridge, United Kingdom, Cambridge University Press, pp. 467-489
  • 'Sanborn, Adam N., 'Zhu, J -Q., 'Spicer, Jake, 'Sundh, Joakim, 'Le?n-Villagr?, Pablo, 'Chater, Nick, 2021. 'Sampling as the human approximation to probabilistic inference. Muggleton, Stephen; Chater, Nicholas (eds.), Human-Like Machine Intelligence, Oxford, Oxford University Press
  • Sanborn, Adam N., Griffiths, Thomas L., 2015. Exploring the structure of mental representations by implementing computer algorithms with people. In Raaijmakers, J. G. W.; Criss, A. H.; Goldstone, R. L.; Nosofsky, R. M.; 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
  • Sanborn, Adam N., 2015. Bayesian models of cognition. In Jaeger, Dieter; Jung, Ranu (eds.), Encyclopedia of Computational Neuroscience, Springer, pp. 624-625
  • Griffiths, Thomas L., Sanborn, Adam N., Canini, Kevin R., Navarro, Daniel J., Tenenbaum, Joshua B., 2011. Nonparametric Bayesian models of categorization. In Pothos, Emmanuel M.; Wills, Andy J. (eds.), Formal Approaches in Categorization, Cambridge, Cambridge University Press, pp. 173-198
  • Griffiths, Thomas L., Canini, Kevin R., Sanborn, Adam N., Navarro, Daniel J., 2009. Unifying rational models of categorization via the hierarchical Dirichlet process. Proceedings of the 29th Annual Conference of the Cognitive Science Society, Mahwah, N.J., Lawrence Erlbaum
  • Heller, Katherine, Sanborn, Adam N., Chater, Nick, 2009. Hierarchical learning of dimensional biases inhuman categorization. Lafferty , J. Clayton (James Clayton), 1928-; 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
  • Sanborn, Adam N., 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
  • Griffiths, Thomas L., Sanborn, Adam N., Canini, Kevin R., Navarro, Daniel J., 2008. Categorization as nonparametric Bayesian density estimation. In Chater, Nick; Oaksford, Mike (eds.), The probabilistic mind : prospects for Bayesian cognitive science, Oxford, Oxford University Press, pp. 303-328
  • Sanborn, Adam N., Griffiths, Thomas L., 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
  • Lloyd, Kevin, Sanborn, Adam N., Leslie, David, Lewandowsky, Stephan, 2017. Why does higher working memory capacity help you learn?. 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
  • Surdina, Alexandra, Sanborn, Adam N., 2017. Temporal variability in moral value judgement. 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
  • Spicer, Jake, Sanborn, Adam N., 2017. A rational approach to stereotype change. 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
  • Tripp, James, Sanborn, Adam N., Stewart, Neil, Noguchi, Takao, 2015. Multiple strategies in conjunction and disjunction judgments : most people are normative part of the time. 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
  • Noguchi, Takao, Sanborn, Adam N., Stewart, Neil, 2013. Non-parametric estimation of the individual's utility map. 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
  • Sanborn, Adam N., Mansinghka, Vikash, Griffiths , Thomas L., 2009. A Bayesian framework for modeling intuitive dynamics. CogSci 2009: 31st Annual Meeting of the Cognitive Science Society, Amsterdam, Netherlands, 29 Jul - 1 Aug 2009
  • Sanborn, Adam N., Silva, Ricardo, 2009. Belief propagation and locally Bayesian learning. 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
  • Martin, Jason, Griffiths , Thomas L., Sanborn, Adam N., 2009. A walk through face space : affect classification using Markov chain Monte Carlo. CogSci 2009: 31st Annual Meeting of the Cognitive Science Society, Amsterdam, Netherlands, 29 Jul - 1 Aug 2009
Title Funder Award start Award end
Searching for the Approximation Method used to Perform rationaL inference by INdividuals and Groups - SAMPLING. ERC-CoG European Research Council 01 Apr 2019 30 Sep 2024
The macroeconomics of the sampling brain - extension ESRC 01 Apr 2020 31 Dec 2020
Macroeconomic Implications of the Sampling Brain ESRC 01 Jan 2019 30 Nov 2019
Combination Rules in Information Integration ESRC 01 Jul 2013 30 Jun 2016