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Angela J. Yu

3 accepted papers

2018

Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation

NeurIPS 2018poster

Understanding how humans and animals learn about statistical regularities in stable and volatile environments, and utilize these regularities to make predictions and decisions, is an important problem in neuroscience and psychology. Using a Bayesian modeling framework, specifically the Dynamic Belie…

Cited by 15SourcePDFScholar
2018

Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task

NeurIPS 2018poster

How humans make repeated choices among options with imperfectly known reward outcomes is an important problem in psychology and neuroscience. This is often studied using multi-armed bandits, which is also frequently studied in machine learning. We present data from a human stationary bandit experime…

Cited by 12SourcePDFScholar