Yael Niv

Orcid: 0000-0002-0259-8371

Affiliations:
  • Princeton University, Princeton Neuroscience Institute and Department of Psychology, USA


According to our database1, Yael Niv authored at least 28 papers between 2001 and 2023.

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Bibliography

2023
Affect-congruent attention modulates generalized reward expectations.
PLoS Comput. Biol., December, 2023

States as goal-directed concepts: an epistemic approach to state-representation learning.
CoRR, 2023

Human inductive biases for aversive continual learning - a hierarchical Bayesian nonparametric model.
Proceedings of the Conference on Lifelong Learning Agents, 2023

2022
Humans combine value learning and hypothesis testing strategically in multi-dimensional probabilistic reward learning.
PLoS Comput. Biol., November, 2022

Minimal cross-trial generalization in learning the representation of an odor-guided choice task.
PLoS Comput. Biol., 2022

2020
Learning what is relevant for rewards via value-based serial hypothesis testing.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019
Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias.
PLoS Comput. Biol., 2019

Gender and collaboration patterns in a temporal scientific authorship network.
Appl. Netw. Sci., 2019

2018
Efficiency of learning vs. processing: Towards a normative theory of multitasking.
Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017
Translating a Reinforcement Learning Task into a Computational Psychiatry Assay: Challenges and Strategies.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016
A Bayesian method for reducing bias in neural representational similarity analysis.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Novelty and Inductive Generalization in Human Reinforcement Learning.
Top. Cogn. Sci., 2015

Is Model Fitting Necessary for Model-Based fMRI?
PLoS Comput. Biol., 2015

2014
Optimal Behavioral Hierarchy.
PLoS Comput. Biol., 2014

Statistical Computations Underlying the Dynamics of Memory Updating.
PLoS Comput. Biol., 2014

2013
Neural and Psychological Maturation of Decision-making in Adolescence and Young Adulthood.
J. Cogn. Neurosci., 2013

Divide and Conquer: Hierarchical Reinforcement Learning and Task Decomposition in Humans.
Proceedings of the Computational and Robotic Models of the Hierarchical Organization of Behavior, 2013

2012
Neural Computations Supporting Cognition: Rumelhart Prize Symposium in Honor of Peter Dayan.
Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011
Computational, Neuroscientific, and Lifespan Perspectives on the Exploration-Exploitation Dilemma.
Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2009
Tutorial summary: The neuroscience of reinforcement learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Operant conditioning.
Scholarpedia, 2008

Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2006
The misbehavior of value and the discipline of the will.
Neural Networks, 2006

2005
How fast to work: Response vigor, motivation and tonic dopamine.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2002
Actor-critic models of the basal ganglia: new anatomical and computational perspectives.
Neural Networks, 2002

Evolution of reinforcement learning in foraging bees: a simple explanation for risk averse behavior.
Neurocomputing, 2002

Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors.
Adapt. Behav., 2002

2001
Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching.
Proceedings of the Advances in Artificial Life, 6th European Conference, 2001


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