| Rational approximations to rational models: alternative algorithms for category learning. AN Sanborn, TL Griffiths, DJ Navarro Psychological review 117 (4), 1144, 2010 | 562 | 2010 |
| Bayesian brains without probabilities AN Sanborn, N Chater Trends in cognitive sciences 20 (12), 883-893, 2016 | 484 | 2016 |
| Bridging levels of analysis for probabilistic models of cognition TL Griffiths, E Vul, AN Sanborn Current Directions in Psychological Science 21 (4), 263-268, 2012 | 281 | 2012 |
| Reconciling intuitive physics and Newtonian mechanics for colliding objects. AN Sanborn, VK Mansinghka, TL Griffiths Psychological review 120 (2), 411, 2013 | 279 | 2013 |
| Deciphering the temporal link between pain and sleep in a heterogeneous chronic pain patient sample: a multilevel daily process study NKY Tang, CE Goodchild, AN Sanborn, J Howard, PM Salkovskis Sleep 35 (5), 675-687, 2012 | 279 | 2012 |
| Exemplar models as a mechanism for performing Bayesian inference L Shi, TL Griffiths, NH Feldman, AN Sanborn Psychonomic bulletin & review 17 (4), 443-464, 2010 | 204 | 2010 |
| A more rational model of categorization AN Sanborn, TL Griffiths, DJ Navarro Proceedings of the 28th annual conference of the cognitive science society …, 2006 | 171 | 2006 |
| The Bayesian sampler: Generic Bayesian inference causes incoherence in human probability judgments. JQ Zhu, AN Sanborn, N Chater Psychological review 127 (5), 719, 2020 | 157 | 2020 |
| Better quality sleep promotes daytime physical activity in patients with chronic pain? A multilevel analysis of the within-person relationship NKY Tang, AN Sanborn PloS one 9 (3), e92158, 2014 | 149 | 2014 |
| Model evaluation using grouped or individual data AL Cohen, AN Sanborn, RM Shiffrin Psychonomic Bulletin & Review 15 (4), 692-712, 2008 | 139 | 2008 |
| Unifying rational models of categorization via the hierarchical Dirichlet process TL Griffiths, KR Canini, AN Sanborn, DJ Navarro Proceedings of the Annual Meeting of the Cognitive Science Society 29 (29), 2007 | 133 | 2007 |
| Uncovering mental representations with Markov chain Monte Carlo AN Sanborn, TL Griffiths, RM Shiffrin Cognitive psychology 60 (2), 63-106, 2010 | 113 | 2010 |
| What sways people’s judgment of sleep quality? A quantitative choice-making study with good and poor sleepers F Ramlee, AN Sanborn, NKY Tang Sleep 40 (7), zsx091, 2017 | 101 | 2017 |
| Environmental support promotes expertise-based mitigation of age differences on pilot communication tasks. DG Morrow, HE Ridolfo, WE Menard, A Sanborn, EAL Stine-Morrow, ... Psychology and Aging 18 (2), 268, 2003 | 100 | 2003 |
| Weighing Outcomes by Time or Against Time? Evaluation Rules in Intertemporal Choice M Scholten, D Read, A Sanborn Cognitive science 38 (3), 399-438, 2014 | 90 | 2014 |
| Bedtime social media use, sleep, and affective wellbeing in young adults: An experience sampling study A Das‐Friebel, A Lenneis, A Realo, A Sanborn, NKY Tang, D Wolke, ... Journal of Child Psychology and Psychiatry 61 (10), 1138-1149, 2020 | 89 | 2020 |
| Markov chain Monte Carlo with people A Sanborn, T Griffiths Advances in neural information processing systems 20, 2007 | 89 | 2007 |
| Probabilistic biases meet the Bayesian brain N Chater, JQ Zhu, J Spicer, J Sundh, P León-Villagrá, A Sanborn Current Directions in Psychological Science 29 (5), 506-512, 2020 | 87 | 2020 |
| The frequentist implications of optional stopping on Bayesian hypothesis tests AN Sanborn, TT Hills Psychonomic bulletin & review 21 (2), 283-300, 2014 | 81 | 2014 |
| Categorization as nonparametric Bayesian density estimation TL Griffiths, AN Sanborn, KR Canini, DJ Navarro The probabilistic mind: Prospects for Bayesian cognitive science, 303-328, 2008 | 80 | 2008 |
nick chaterProfessor of Behavioural Science, Warwick Business SchoolVerified email at wbs.ac.uk
