NIPS Proceedings
^{β}
Books
Peter Dayan
48 Papers
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
(2018)
Bayes-Adaptive Simulation-based Search with Value Function Approximation
(2014)
Correlations strike back (again): the case of associative memory retrieval
(2013)
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search
(2012)
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories
(2011)
Know Thy Neighbour: A Normative Theory of Synaptic Depression
(2009)
Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing
(2009)
Bayesian Model of Behaviour in Economic Games
(2008)
Load and Attentional Bayes
(2008)
Psychiatry: Insights into depression through normative decision-making models
(2008)
Hippocampal Contributions to Control: The Third Way
(2007)
Uncertainty, phase and oscillatory hippocampal recall
(2006)
A Bayesian Framework for Tilt Perception and Confidence
(2005)
How fast to work: Response vigor, motivation and tonic dopamine
(2005)
Norepinephrine and Neural Interrupts
(2005)
Assignment of Multiplicative Mixtures in Natural Images
(2004)
Inference, Attention, and Decision in a Bayesian Neural Architecture
(2004)
Probabilistic Computation in Spiking Populations
(2004)
Rate- and Phase-coded Autoassociative Memory
(2004)
Dopamine Modulation in a Basal Ganglio-Cortical Network of Working Memory
(2003)
Plasticity Kernels and Temporal Statistics
(2003)
Adaptation and Unsupervised Learning
(2002)
Expected and Unexpected Uncertainty: ACh and NE in the Neocortex
(2002)
Replay, Repair and Consolidation
(2002)
ACh, Uncertainty, and Cortical Inference
(2001)
Motivated Reinforcement Learning
(2001)
Competition and Arbors in Ocular Dominance
(2000)
Dopamine Bonuses
(2000)
Explaining Away in Weight Space
(2000)
Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex
(2000)
Position Variance, Recurrence and Perceptual Learning
(2000)
Acquisition in Autoshaping
(1999)
Computational Differences between Asymmetrical and Symmetrical Networks
(1998)
Distributional Population Codes and Multiple Motion Models
(1998)
Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning
(1997)
Statistical Models of Conditioning
(1997)
A Hierarchical Model of Visual Rivalry
(1996)
Analytical Mean Squared Error Curves in Temporal Difference Learning
(1996)
Neural Models for Part-Whole Hierarchies
(1996)
Probabilistic Interpretation of Population Codes
(1996)
Does the Wake-sleep Algorithm Produce Good Density Estimators?
(1995)
Improving Policies without Measuring Merits
(1995)
Recognizing Handwritten Digits Using Mixtures of Linear Models
(1994)
Foraging in an Uncertain Environment Using Predictive Hebbian Learning
(1993)
Temporal Difference Learning of Position Evaluation in the Game of Go
(1993)
Feudal Reinforcement Learning
(1992)
Perturbing Hebbian Rules
(1991)
Navigating through Temporal Difference
(1990)