Adam Sanborn - RankMe

39 papers A* 1B 29Journal 6Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Large Language Models Can Take False First Steps at Inference-time Planning. CoRR Haijiang Yan, Jian-Qiao Zhu, Adam Sanborn
2026	J	`jnl`	PriorProbe: Recovering Individual-Level Priors for Personalizing Neural Networks in Facial Expression Recognition. CoRR Haijiang Yan, Nick Chater, Adam Sanborn
2024	B	`conf`	Bias in Belief Updating: Combining the Bayesian Sampler with Heuristics. CogSci Yitong Lin, Jian-Qiao Zhu, Adam Sanborn
2024	B	`conf`	Capturing Asymmetric Bias in Probability Judgements. CogSci Aidan Tee, Joakim Sundh, Adam Sanborn, Nick Chater
2024	B	`conf`	Distinguishing Between Process Models of Causal Learning. CogSci Simon Valentin, Lucas Castillo, Adam Sanborn, Chris Lucas
2024	J	`jnl`	Explaining the flaws in human random generation as local sampling with momentum. PLoS Comput. Biol. Lucas Castillo, Pablo León-Villagrá, Nick Chater, Adam Sanborn
2024	B	`conf`	Mental Sampling in Preferential Choice: Specifying the Sampling Algorithm. CogSci Jake Spicer, Yun-Xiao Li, Lucas Castillo, Johanna Falben, Cheng Stella Qian, Jian-Qiao Zhu, Nick Chater, Adam Sanborn
2024	B	`conf`	Modelling probability matching as a Bayesian sampling process. CogSci Christian Tsvetkov, Haijiang Yan, Adam Sanborn
2024	B	`conf`	People Need About Five Seconds to be Random: Autocorrelated Sampling Algorithms Can Explain Why. CogSci Lucas Castillo, Pablo León-Villagrá, Johanna Falben, Nick Chater, Adam Sanborn
2024	B	`conf`	Probability, but not utility, influences repeated mental simulations of risky events. CogSci Yun-Xiao Li, Johanna Falben, Lucas Castillo, Jake Spicer, Jian-Qiao Zhu, Nick Chater, Adam Sanborn
2024	B	`conf`	Randomly Generating Stereotypes: Can We Understand Implicit Attitudes with Random Generation? CogSci Johanna Falben, Lucas Castillo, Pablo León-Villagrá, Nick Chater, Adam Sanborn
2024	B	`conf`	Recovering individual mental representations of facial affect using Variational Auto-Encoder Guided Markov Chain Monte Carlo with People. CogSci Haijiang Yan, Nick Chater, Christian Tsvetkov, Adam Sanborn
2024	B	`conf`	Unraveling Overreaction in Expectations: Leveraging Cognitive Sampling Algorithms in Price Prediction Tasks. CogSci Yuqi Zhou, Jian-Qiao Zhu, Jake Spicer, Adam Sanborn
2023	B	`conf`	Computation-Limited Bayesian Updating. CogSci Jian-Qiao Zhu, Adam Sanborn, Nick Chater, Tom Griffiths
2023	B	`conf`	The Impact of Production Rates on Sequential Statistics and Distributional Properties in Random Generation. CogSci Pablo León-Villagrá, Lucas Castillo, Nick Chater, Adam Sanborn
2022	B	`conf`	Eliciting Human Beliefs using Random Generation. CogSci Pablo León-Villagrá, Lucas Castillo, Nick Chater, Adam Sanborn
2022	—	`ch.`	Sampling as the Human Approximation to Probabilistic Inference. Human-Like Machine Intelligence Adam Sanborn, Jian-Qiao Zhu, Jake Spicer, Joakim Sundh, Pablo León-Villagrá, Nick Chater
2021	B	`conf`	Local Sampling with Momentum Accounts for Human Random Sequence Generation. CogSci Lucas Castillo, Pablo León-Villagrá, Nicholas Chater, Adam Sanborn
2021	B	`conf`	Sampling Associations with (Un)related Suggestions. CogSci Pablo León-Villagrá, Nicholas Chater, Adam Sanborn
2020	B	`conf`	How many instances come to mind when making probability estimates? CogSci Joakim Sundh, Jian-Qiao Zhu, Nicholas Chater, Adam Sanborn
2019	B	`conf`	Bayesian Inference Causes Incoherence in Human Probability Judgments. CogSci Jian-Qiao Zhu, Adam Sanborn, Nicholas Chater
2019	B	`conf`	Exploring the Representation of Linear Functions. CogSci Pablo León-Villagrá, Verena Klar, Adam Sanborn, Chris Lucas
2019	B	`conf`	Using Occam's razor and Bayesian modelling to compare discrete and continuous representations in numerostiy judgements. CogSci Jake Spicer, Adam Sanborn, Ulrik R. Beierholm
2019	B	`conf`	Why Decisions Bias Perception: An Amortised Sequential Sampling Account. CogSci Jian-Qiao Zhu, Adam Sanborn, Nick Chater
2019	J	`jnl`	Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation. Cogn. Sci. Kevin Lloyd, Adam Sanborn, David S. Leslie, Stephan Lewandowsky
2018	A*	`conf`	Mental Sampling in Multimodal Representations. NeurIPS Jian-Qiao Zhu, Adam Sanborn, Nick Chater
2017	B	`conf`	A Rational Approach to Stereotype Change. CogSci Jake Spicer, Adam Sanborn
2017	B	`conf`	Temporal variability in moral value judgement. CogSci Alexandra Surdina, Adam Sanborn
2017	B	`conf`	Why Does Higher Working Memory Capacity Help You Learn? CogSci Kevin Lloyd, Adam Sanborn, David S. Leslie, Stephan Lewandowsky
2016	B	`conf`	Choosing Poorly: Reward-Induced Strategy Shifts in Estimating the Probabilities of Conjunctions and Disjunctions. CogSci James Tripp, Adam Sanborn, Neil Stewart, Takao Noguchi
2015	B	`conf`	Inference, Not Dilution in the Dilution Effect. CogSci Adam Sanborn, Takao Noguchi, James Tripp, Neil Stewart
2015	B	`conf`	Multiple Strategies in Conjunction and Disjunction Judgments: Most People are Normative Part of the Time. CogSci James Tripp, Adam Sanborn, Neil Stewart, Takao Noguchi
2014	J	`jnl`	Weighing Outcomes Cogn. Sci. Marc Scholten, Daniel Read, Adam Sanborn
2013	B	`conf`	Non-parametric estimation of the individual's utility map. CogSci Takao Noguchi, Adam Sanborn, Neil Stewart
2012	B	`conf`	Computational Models of Intuitive Physics. CogSci Peter W. Battaglia, Tomer D. Ullman, Joshua B. Tenenbaum, Adam Sanborn, Kenneth D. Forbus, Tobias Gerstenberg, David A. Lagnado
2012	B	`conf`	Look-Ahead Monte Carlo with People. CogSci Charles Blundell, Adam Sanborn, Thomas L. Griffiths
2012	J	`jnl`	Testing the Efficiency of Markov Chain Monte Carlo With People Using Facial Affect Categories. Cogn. Sci. Jay B. Martin, Thomas L. Griffiths, Adam Sanborn
2009	—	`conf`	Hierarchical Learning of Dimensional Biases in Human Categorization. NIPS Katherine A. Heller, Adam Sanborn, Nick Chater
2007	—	`conf`	Markov Chain Monte Carlo with People. NIPS Adam Sanborn, Thomas L. Griffiths