Navigating Through Temporal Difference. - Peter Dayan (NIPS, 1990)

Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down. - David J. Willshaw; Peter Dayan (Neural Comput., 1990)

Perturbing Hebbian Rules. - Peter Dayan; Geoffrey J. Goodhill (NIPS, 1991)

Optimising synaptic learning rules in linear associative memories. - Peter Dayan; David J. Willshaw (Biol. Cybern., 1991)

Feudal Reinforcement Learning. - Peter Dayan; Geoffrey E. Hinton (NIPS, 1992)

Using Aperiodic Reinforcement for Directed Self-Organization During Development. - P. Read Montague; Peter Dayan; Steven J. Nowlan; Terrence J. Sejnowski (NIPS, 1992)

The Convergence of TD(lambda) for General lambda. - Peter Dayan (Mach. Learn., 1992)

Technical Note Q-Learning. - Christopher J. C. H. Watkins; Peter Dayan (Mach. Learn., 1992)

Foraging in an Uncertain Environment Using Predictive Hebbian Learning. - P. Read Montague; Peter Dayan; Terrence J. Sejnowski (NIPS, 1993)

Temporal Difference Learning of Position Evaluation in the Game of Go. - Nicol N. Schraudolph; Peter Dayan; Terrence J. Sejnowski (NIPS, 1993)

Arbitrary Elastic Topologies and Ocular Dominance. - Peter Dayan (Neural Comput., 1993)

Improving Generalization for Temporal Difference Learning: The Successor Representation. - Peter Dayan (Neural Comput., 1993)

The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. - Peter Dayan; Terrence J. Sejnowski (Neural Comput., 1993)

Recognizing Handwritten Digits Using Mixtures of Linear Models. - Geoffrey E. Hinton; Michael Revow; Peter Dayan (NIPS, 1994)

TD(lambda) Converges with Probability 1. - Peter Dayan; Terrence J. Sejnowski (Mach. Learn., 1994)

Predictive Hebbian Learning. - Terrence J. Sejnowski; Peter Dayan; P. Read Montague (COLT, 1995)

Improving Policies without Measuring Merits. - Peter Dayan; Satinder Singh 001 (NIPS, 1995)

Does the Wake-sleep Algorithm Produce Good Density Estimators? - Brendan J. Frey; Geoffrey E. Hinton; Peter Dayan (NIPS, 1995)

The Helmholtz machine. - Peter Dayan; Geoffrey E. Hinton; Radford M. Neal; Richard S. Zemel (Neural Comput., 1995)

Competition and Multiple Cause Models. - Peter Dayan; Richard S. Zemel (Neural Comput., 1995)

A Hierarchical Model of Visual Rivalry. - Peter Dayan (NIPS, 1996)

Neural Models for Part-Whole Hierarchies. - Maximilian Riesenhuber; Peter Dayan (NIPS, 1996)

Exploration Bonuses and Dual Control. - Peter Dayan; Terrence J. Sejnowski (Mach. Learn., 1996)

Varieties of Helmholtz Machine. - Peter Dayan; Geoffrey E. Hinton (Neural Networks, 1996)

Combining Probabilistic Population Codes. - Richard S. Zemel; Peter Dayan (IJCAI, 1997)

Statistical Models of Conditioning. - Peter Dayan; Theresa Long (NIPS, 1997)

Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning. - David J. Foster; Richard G. M. Morris; Peter Dayan (NIPS, 1997)

Using Expectation-Maximization for Reinforcement Learning. - Peter Dayan; Geoffrey E. Hinton (Neural Comput., 1997)

Factor Analysis Using Delta-Rule Wake-Sleep Learning. - Radford M. Neal; Peter Dayan (Neural Comput., 1997)

Modeling the manifolds of images of handwritten digits. - Geoffrey E. Hinton; Peter Dayan; Michael Revow (IEEE Trans. Neural Networks, 1997)

Computational Differences between Asymmetrical and Symmetrical Networks. - Zhaoping Li 001; Peter Dayan (NIPS, 1998)

Distributional Population Codes and Multiple Motion Models. - Richard S. Zemel; Peter Dayan (NIPS, 1998)

Analytical Mean Squared Error Curves for Temporal Difference Learning. - Satinder Singh 001; Peter Dayan (Mach. Learn., 1998)

A Hierarchical Model of Binocular Rivalry. - Peter Dayan (Neural Comput., 1998)

Probabilistic Interpretation of Population Codes. - Richard S. Zemel; Peter Dayan; Alexandre Pouget (Neural Comput., 1998)

Bayesian retrieval in associative memories with storage errors. - Friedrich T. Sommer; Peter Dayan (IEEE Trans. Neural Networks, 1998)

Acquisition in Autoshaping. - Sham M. Kakade; Peter Dayan (NIPS, 1999)

The Effect of Correlated Variability on the Accuracy of a Population Code. - L. F. Abbott; Peter Dayan (Neural Comput., 1999)

Recurrent Sampling Models for the Helmholtz Machine. - Peter Dayan (Neural Comput., 1999)

Competition and Arbors in Ocular Dominance. - Peter Dayan (NIPS, 2000)

Explaining Away in Weight Space. - Peter Dayan; Sham M. Kakade (NIPS, 2000)

Dopamine Bonuses. - Sham M. Kakade; Peter Dayan (NIPS, 2000)

Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex. - Szabolcs Káli; Peter Dayan (NIPS, 2000)

Position Variance, Recurrence and Perceptual Learning. - Zhaoping Li 001; Peter Dayan (NIPS, 2000)

Motivated Reinforcement Learning. - Peter Dayan (NIPS, 2001)

ACh, Uncertainty, and Cortical Inference. - Peter Dayan; Angela J. Yu (NIPS, 2001)

A familiarity-based learning procedure for the establishment of place fields in area CA3 of the rat hippocampus. - Szabolcs Káli; Peter Dayan (Neurocomputing, 2001)

Adaptation and Unsupervised Learning. - Peter Dayan; Maneesh Sahani; Gregoire Deback (NIPS, 2002)

Replay, Repair and Consolidation. - Szabolcs Káli; Peter Dayan (NIPS, 2002)

Expected and Unexpected Uncertainty: ACh and NE in the Neocortex. - Angela J. Yu; Peter Dayan (NIPS, 2002)

Structure in the Space of Value Functions. - David J. Foster; Peter Dayan (Mach. Learn., 2002)

Opponent interactions between serotonin and dopamine. - Nathaniel D. Daw; Sham M. Kakade; Peter Dayan (Neural Networks, 2002)

Introduction for 2002 Special Issue: Computational Models of Neuromodulation. - Kenji Doya; Peter Dayan; Michael E. Hasselmo (Neural Networks, 2002)

Dopamine: generalization and bonuses. - Sham M. Kakade; Peter Dayan (Neural Networks, 2002)

Acetylcholine in cortical inference. - Angela J. Yu; Peter Dayan (Neural Networks, 2002)

Plasticity Kernels and Temporal Statistics. - Peter Dayan; Michael Häusser (NIPS, 2003)

Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory. - Aaron J. Gruber; Peter Dayan; Boris S. Gutkin; Sara A. Solla (NIPS, 2003)

Doubly Distributional Population Codes: Simultaneous Representation of Uncertainty and Multiplicity. - Maneesh Sahani; Peter Dayan (Neural Comput., 2003)

Rate- and Phase-coded Autoassociative Memory. - Máté Lengyel; Peter Dayan (NIPS, 2004)

Assignment of Multiplicative Mixtures in Natural Images. - Odelia Schwartz; Terrence J. Sejnowski; Peter Dayan (NIPS, 2004)

Inference, Attention, and Decision in a Bayesian Neural Architecture. - Angela J. Yu; Peter Dayan (NIPS, 2004)

Probabilistic Computation in Spiking Populations. - Richard S. Zemel; Quentin J. M. Huys; Rama Natarajan; Peter Dayan (NIPS, 2004)

Differential Priors for Elastic Nets. - Miguel Á. Carreira-Perpiñán; Peter Dayan; Geoffrey J. Goodhill (IDEAL, 2005)

Norepinephrine and Neural Interrupts. - Peter Dayan; Angela J. Yu (NIPS, 2005)

How fast to work: Response vigor, motivation and tonic dopamine. - Yael Niv; Nathaniel D. Daw; Peter Dayan (NIPS, 2005)

A Bayesian Framework for Tilt Perception and Confidence. - Odelia Schwartz; Terrence J. Sejnowski; Peter Dayan (NIPS, 2005)

Uncertainty, phase and oscillatory hippocampal recall. - Máté Lengyel; Peter Dayan (NIPS, 2006)

Dopamine modulation in the basal ganglia locks the gate to working memory. - Aaron J. Gruber; Peter Dayan; Boris S. Gutkin; Sara A. Solla (J. Comput. Neurosci., 2006)

Images, Frames, and Connectionist Hierarchies. - Peter Dayan (Neural Comput., 2006)

Soft Mixer Assignment in a Hierarchical Generative Model of Natural Scene Statistics. - Odelia Schwartz; Terrence J. Sejnowski; Peter Dayan (Neural Comput., 2006)

The misbehavior of value and the discipline of the will. - Peter Dayan; Yael Niv; Ben Seymour; Nathaniel D. Daw (Neural Networks, 2006)

Pre-attentive visual selection. - Zhaoping Li 001; Peter Dayan (Neural Networks, 2006)

Hippocampal Contributions to Control: The Third Way. - Máté Lengyel; Peter Dayan (NIPS, 2007)

Bilinearity, rules, and prefrontal cortex. - Peter Dayan (Frontiers Comput. Neurosci., 2007)

Fast Population Coding. - Quentin J. M. Huys; Richard S. Zemel; Rama Natarajan; Peter Dayan (Neural Comput., 2007)

Load and Attentional Bayes. - Peter Dayan (NIPS, 2008)

Psychiatry: Insights into depression through normative decision-making models. - Quentin J. M. Huys; Joshua T. Vogelstein; Peter Dayan (NIPS, 2008)

Bayesian Model of Behaviour in Economic Games. - Debajyoti Ray; Brooks King-Casas; P. Read Montague; Peter Dayan (NIPS, 2008)

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis. - Marzia De Lucia; Juan Fritschy; Peter Dayan; David S. Holder (Medical Biol. Eng. Comput., 2008)

Encoding and Decoding Spikes for Dynamic Stimuli. - Rama Natarajan; Quentin J. M. Huys; Peter Dayan; Richard S. Zemel (Neural Comput., 2008)

Serotonin, Inhibition, and Negative Mood. - Peter Dayan; Quentin J. M. Huys (PLoS Comput. Biol., 2008)

Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing. - Ruben Coen Cagli; Peter Dayan; Odelia Schwartz (NIPS, 2009)

Know Thy Neighbour: A Normative Theory of Synaptic Depression. - Jean-Pascal Pfister; Peter Dayan; Máté Lengyel (NIPS, 2009)

Goal-directed control and its antipodes. - Peter Dayan (Neural Networks, 2009)

Change-Based Inference in Attractor Nets: Linear Analysis. - Reza Moazzezi; Peter Dayan (Neural Comput., 2010)

Pavlovian-Instrumental Interaction in 'Observing Behavior'. - Ulrik R. Beierholm; Peter Dayan (PLoS Comput. Biol., 2010)

Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories. - Cristina Savin; Peter Dayan; Máté Lengyel (NIPS, 2011)

Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131). - Jeremy L. Wyatt; Peter Dayan; Ales Leonardis; Jan Peters 001 (Dagstuhl Reports, 2011)

Vigor in the Face of Fluctuating Rates of Reward: An Experimental Examination. - Marc Guitart-Masip; Ulrik R. Beierholm; Raymond J. Dolan; Emrah Düzel; Peter Dayan (J. Cogn. Neurosci., 2011)

Bayes-Optimal Chemotaxis. - Duncan Mortimer; Peter Dayan; Kevin Burrage; Geoffrey J. Goodhill (Neural Comput., 2011)

Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding. - Quentin J. M. Huys; Roshan Cools; Martin Gölzer; Eva Friedel; Andreas Heinz; Raymond J. Dolan; Peter Dayan (PLoS Comput. Biol., 2011)

Computational, Cognitive, and Neural Models of Decision-making Biases. - Jonathan Malmaud; Joshua B. Tenenbaum; Peter Dayan; Laurence T. Maloney; Edward Vul; Nick Chater (CogSci, 2012)

Dynamic decision making: neuronal, computational, and cognitive underpinnings. - Magda Osman; Maarten Speekenbrink; Peter Dayan; Masataka Watanabe; Nigel Harvey (CogSci, 2012)

An Activity Theory Based Analysis of Work Activities in the Emergency Department. - Barbara Sheehan; Lise E. Nigrovic; Peter S. Dayan; Nathan Kuppermann; Dustin W. Ballard; Evaline Alessandrini; Lalit Bajaj; Howard Goldberg; Jeffrey Hoffman; Steven R. Offerman; Dustin G. Mark; Marguerite Swietlik; et al. (Nursing Informatics, 2012)

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. - Arthur Guez; David Silver; Peter Dayan (NIPS, 2012)

Go and no-go learning in reward and punishment: Interactions between affect and effect. - Marc Guitart-Masip; Quentin J. M. Huys; Lluís Fuentemilla; Peter Dayan; Emrah Düzel; Raymond J. Dolan (NeuroImage, 2012)

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics. - Ruben Coen Cagli; Peter Dayan; Odelia Schwartz (PLoS Comput. Biol., 2012)

Bonsai Trees in Your Head: How the Pavlovian System Sculpts Goal-Directed Choices by Pruning Decision Trees. - Quentin J. M. Huys; Neir Eshel; Elizabeth J. P. O'Nions; Luke Sheridan; Peter Dayan; Jonathan P. Roiser (PLoS Comput. Biol., 2012)

Computational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thought. - Ting Xiang; Debajyoti Ray; Terry Lohrenz; Peter Dayan; P. Read Montague (PLoS Comput. Biol., 2012)

Exploration from Generalization Mediated by Multiple Controllers. - Peter Dayan (Intrinsically Motivated Learning in Natural and Artificial Systems, 2013)

Structured cognitive representations and complex inference in neural systems. - Samuel Gershman; Joshua B. Tenenbaum; Alexandre Pouget; Matthew M. Botvinick; Peter Dayan (CogSci, 2013)

Correlations strike back (again): the case of associative memory retrieval. - Cristina Savin; Peter Dayan; Máté Lengyel (NIPS, 2013)

Scalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search. - Arthur Guez; David Silver; Peter Dayan (J. Artif. Intell. Res., 2013)

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: A sociotechnical analysis. - Barbara Sheehan; Lise E. Nigrovic; Peter S. Dayan; Nathan Kuppermann; Dustin W. Ballard; Evaline Alessandrini; Lalit Bajaj; Howard Goldberg; Jeffrey Hoffman; Steven R. Offerman; Dustin G. Mark; Marguerite Swietlik; et al. (J. Biomed. Informatics, 2013)

Sparse Coding Can Predict Primary Visual Cortex Receptive Field Changes Induced by Abnormal Visual Input. - Jonathan J. Hunt; Peter Dayan; Geoffrey J. Goodhill (PLoS Comput. Biol., 2013)

Bayes-Adaptive Simulation-based Search with Value Function Approximation. - Arthur Guez; Nicolas Heess; David Silver; Peter Dayan (NIPS, 2014)

Better Optimism By Bayes: Adaptive Planning with Rich Models. - Arthur Guez; David Silver; Peter Dayan (CoRR, 2014)

Some Work and Some Play: Microscopic and Macroscopic Approaches to Labor and Leisure. - Ritwik K. Niyogi; Peter Shizgal; Peter Dayan (PLoS Comput. Biol., 2014)

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3. - Cristina Savin; Peter Dayan; Máté Lengyel (PLoS Comput. Biol., 2014)

Rationalizable Irrationalities of Choice. - Peter Dayan (Top. Cogn. Sci., 2014)

Staying afloat on Neurath's boat - Heuristics for sequential causal learning. - Neil Bramley; Peter Dayan; David A. Lagnado (CogSci, 2015)

Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task. - Thomas E. Akam; Rui Costa; Peter Dayan (PLoS Comput. Biol., 2015)

Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange. - Andreas Hula; P. Read Montague; Peter Dayan (PLoS Comput. Biol., 2015)

Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens. - Kevin Lloyd; Peter Dayan (PLoS Comput. Biol., 2015)

A Probabilistic Palimpsest Model of Visual Short-term Memory. - Loic Matthey; Paul M. Bays; Peter Dayan (PLoS Comput. Biol., 2015)

Anticipation and Choice Heuristics in the Dynamic Consumption of Pain Relief. - Giles W. Story; Ivo Vlaev; Peter Dayan; Ben Seymour; Ara Darzi; Raymond J. Dolan (PLoS Comput. Biol., 2015)

Clinical Decision Support for a Multicenter Trial of Pediatric Head Trauma. - Marguerite Swietlik; Sara J. Deakyne Davies; Jeffrey Hoffman; Robert Grundmeier; Marilyn D. Paterno; Beatriz H. Rocha; Molly Schaeffer; Deepika Pabbathi; Evaline Alessandrini; Dustin Ballard; Howard Goldberg; Nathan Kuppermann; et al. (Appl. Clin. Inform., 2016)

Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning. - Neil R. Bramley; Peter Dayan; Thomas L. Griffiths 001; David A. Lagnado (CoRR, 2016)

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma. - Howard S. Goldberg; Marilyn D. Paterno; Robert Grundmeier; Beatriz H. Rocha; Jeffrey Hoffman; Eric Tham; Marguerite Swietlik; Molly Schaeffer; Deepika Pabbathi; Sara J. Deakyne Davies; Nathan Kuppermann; Peter S. Dayan (Int. J. Medical Informatics, 2016)

The Dopaminergic Midbrain Mediates an Effect of Average Reward on Pavlovian Vigor. - Francesco Rigoli; Benjamin Chew; Peter Dayan; Raymond J. Dolan (J. Cogn. Neurosci., 2016)

Multiple value signals in dopaminergic midbrain and their role in avoidance contexts. - Francesco Rigoli; Benjamin Chew; Peter Dayan; Raymond J. Dolan (NeuroImage, 2016)

The influence of contextual reward statistics on risk preference. - Francesco Rigoli; Robb B. Rutledge; Peter Dayan; Raymond J. Dolan (NeuroImage, 2016)

How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences. - Michael Moutoussis; Raymond J. Dolan; Peter Dayan (PLoS Comput. Biol., 2016)

A model of structure learning, inference, and generation for scene understanding. - David Raposo; Peter Dayan; Demis Hassabis; Peter W. Battaglia (CogSci, 2017)

Comparison of Maximum Likelihood and GAN-based training of Real NVPs. - Ivo Danihelka; Balaji Lakshminarayanan; Benigno Uria; Daan Wierstra; Peter Dayan (CoRR, 2017)

Increased decision thresholds enhance information gathering performance in juvenile Obsessive-Compulsive Disorder (OCD). - Tobias U. Hauser; Michael Moutoussis; Reto Iannaccone; Silvia Brem; Susanne Walitza; Renate Drechsler; Peter Dayan; Raymond J. Dolan (PLoS Comput. Biol., 2017)

Fast Parametric Learning with Activation Memorization. - Jack W. Rae; Chris Dyer; Peter Dayan; Timothy P. Lillicrap (ICML, 2018)

Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models. - Amir Dezfouli; Richard W. Morris; Fabio T. Ramos 001; Peter Dayan; Bernard W. Balleine (NeurIPS, 2018)

Applying the RE-AIM Framework for the Evaluation of a Clinical Decision Support Tool for Pediatric Head Trauma: A Mixed-Methods Study. - Ruth Masterson Creber; Peter Dayan; Nathan Kuppermann; Dustin W. Ballard; Leah Tzimenatos; Evaline Alessandrini; Rakesh Mistry; Jeffrey Hoffman; David R. Vinson; Suzanne Bakken (Appl. Clin. Inform., 2018)

Examining Workflow in a Pediatric Emergency Department to Develop a Clinical Decision Support for an Antimicrobial Stewardship Program. - Mustafa Ozkaynak; Danny Wu; Katia Hannah; Peter Dayan; Rakesh Mistry (Appl. Clin. Inform., 2018)

Probabilistic Meta-Representations Of Neural Networks. - Theofanis Karaletsos; Peter Dayan; Zoubin Ghahramani (CoRR, 2018)

Learning Contextual Reward Expectations for Value Adaptation. - Francesco Rigoli; Benjamin Chew; Peter Dayan; Raymond J. Dolan (J. Cogn. Neurosci., 2018)

Control of neurite growth and guidance by an inhibitory cell-body signal. - Brendan A. Bicknell; Zac Pujic; Peter Dayan; Geoffrey J. Goodhill (PLoS Comput. Biol., 2018)

A model of risk and mental state shifts during social interaction. - Andreas Hula; Iris Vilares; Terry Lohrenz; Peter Dayan; P. Read Montague (PLoS Comput. Biol., 2018)

Interrupting behaviour: Minimizing decision costs via temporal commitment and low-level interrupts. - Kevin Lloyd; Peter Dayan (PLoS Comput. Biol., 2018)

Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood. - Michael Moutoussis; Edward T. Bullmore; Ian M. Goodyer; Peter Fonagy; Peter B. Jones; Raymond J. Dolan; Peter Dayan (PLoS Comput. Biol., 2018)

Disentangled behavioural representations. - Amir Dezfouli; Hassan Ashtiani; Omar Ghattas; Richard Nock; Peter Dayan; Cheng Soon Ong (NeurIPS, 2019)

Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. - Sanjeevan Ahilan; Peter Dayan (CoRR, 2019)

Prefrontal Dynamics Associated with Efficient Detours and Shortcuts: A Combined Functional Magnetic Resonance Imaging and Magnetoencenphalography Study. - Amir Homayoun Javadi; Eva Zita Patai; Eugenia Marin-Garcia; Aaron Margolis; Heng-Ru May Tan; Dharshan Kumaran; Marko Nardini; Will D. Penny; Emrah Düzel; Peter S. Dayan; Hugo J. Spiers (J. Cogn. Neurosci., 2019)

Learning to use past evidence in a sophisticated world model. - Sanjeevan Ahilan; Rebecca B. Solomon; Yannick-André Breton; Kent L. Conover; Ritwik K. Niyogi; Peter Shizgal; Peter Dayan (PLoS Comput. Biol., 2019)

Models that learn how humans learn: The case of decision-making and its disorders. - Amir Dezfouli; Kristi Griffiths; Fabio Ramos 001; Peter Dayan; Bernard W. Balleine (PLoS Comput. Biol., 2019)

A computational account of threat-related attentional bias. - Toby Wise; Jochen Michely; Peter Dayan; Raymond J. Dolan (PLoS Comput. Biol., 2019)

A Local Temporal Difference Code for Distributional Reinforcement Learning. - Pablo Tano; Peter Dayan; Alexandre Pouget (NeurIPS, 2020)

Static and Dynamic Values of Computation in MCTS. - Eren Sezener; Peter Dayan (UAI, 2020)

Considerations for Designing EHR-Embedded Clinical Decision Support Systems for Antimicrobial Stewardship in Pediatric Emergency Departments. - Mustafa Ozkaynak; Noel Metcalf; Daniel M. Cohen; Larissa S. May; Peter S. Dayan; Rakesh Mistry (Appl. Clin. Inform., 2020)

Combined model-free and model-sensitive reinforcement learning in non-human primates. - Bruno Miranda; W. M. Nishantha Malalasekera; Timothy Edward John Behrens; Peter Dayan; Steven W. Kennerley (PLoS Comput. Biol., 2020)

Exploring learning trajectories with dynamic infinite hidden Markov models. - Sebastian A. Bruijns; International Brain Laboratory; Peter Dayan (CogSci, 2021)

Tracking the Unknown: Modeling Long-Term Implicit Skill Acquisition as Non-Parametric Bayesian Sequence Learning. - Noémi Élteto; Dezso Németh; Karolina Janacsek; Peter Dayan (CogSci, 2021)

Confidence in control: Metacognitive computations for information search. - Lion Schulz; Stephen M. Fleming; Peter Dayan (CogSci, 2021)

Correcting experience replay for multi-agent communication. - Sanjeevan Ahilan; Peter Dayan (ICLR, 2021)

Two steps to risk sensitivity. - Chris Gagne 001; Peter Dayan (NeurIPS, 2021)

Catastrophe, Compounding & Consistency in Choice. - Chris Gagne 001; Peter Dayan (CoRR, 2021)

Using Primary Reinforcement to Enhance Translatability of a Human Affect and Decision-Making Judgment Bias Task. - Vikki Neville; Peter Dayan; Iain D. Gilchrist; Elizabeth S. Paul; Michael Mendl (J. Cogn. Neurosci., 2021)

Internality and the internalisation of failure: Evidence from a novel task. - Federico Mancinelli; Jonathan P. Roiser; Peter Dayan (PLoS Comput. Biol., 2021)

Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach. - Vikki Neville; Peter Dayan; Iain D. Gilchrist; Elizabeth S. Paul; Michael Mendl (PLoS Comput. Biol., 2021)

Neural Network Poisson Models for Behavioural and Neural Spike Train Data. - Moein Khajehnejad; Forough Habibollahi; Richard Nock; Ehsan Arabzadeh; Peter Dayan; Amir Dezfouli (ICML, 2022)

Optimism and pessimism in optimised replay. - Georgy Antonov; Christopher Gagne; Eran Eldar; Peter Dayan (PLoS Comput. Biol., 2022)

The pursuit of happiness: A reinforcement learning perspective on habituation and comparisons. - Rachit Dubey; Thomas L. Griffiths 001; Peter Dayan (PLoS Comput. Biol., 2022)

Biased belief priors versus biased belief updating: Differential correlates of depression and anxiety. - Christopher Gagne; Sharon Agai; Christian Ramiro; Peter Dayan; Sonia J. Bishop (PLoS Comput. Biol., 2022)

Interactions between attributions and beliefs at trial-by-trial level: Evidence from a novel computer game task. - Elena Zamfir; Peter Dayan (PLoS Comput. Biol., 2022)

Vigilance, arousal, and acetylcholine: Optimal control of attention in a simple detection task. - Sahiti Chebolu; Peter Dayan; Kevin Lloyd (PLoS Comput. Biol., 2022)

Tracking human skill learning with a hierarchical Bayesian sequence model. - Noémi Élteto; Dezso Németh; Karolina Janacsek; Peter Dayan (PLoS Comput. Biol., 2022)

Habits of Mind: Reusing Action Sequences for Efficient Planning. - Noémi Élteto; Peter Dayan (CogSci, 2023)

Compositionality under time pressure. - Valerio Rubino; Mani Hamidi; Peter Dayan; Charley M. Wu (CogSci, 2023)

Reinforcement Learning with Simple Sequence Priors. - Tankred Saanum; Noémi Élteto; Peter Dayan; Marcel Binz; Eric Schulz (NeurIPS, 2023)

The Inner Sentiments of a Thought. - Chris Gagne 001; Peter Dayan (CoRR, 2023)

Reframing dopamine: A controlled controller at the limbic-motor interface. - Kevin Lloyd; Peter Dayan (PLoS Comput. Biol., 2023)

Characterising the Creative Process in Humans and Large Language Models. - Surabhi S. Nath; Peter Dayan; Claire E. Stevenson (ICCC, 2024)

Simplifying Latent Dynamics with Softly State-Invariant World Models. - Tankred Saanum; Peter Dayan; Eric Schulz (NeurIPS, 2024)

Exploring Uncertainty in Distributional Reinforcement Learning. - Georgy Antonov; Peter Dayan (RLJ, 2024)

Predicting the Future with Simple World Models. - Tankred Saanum; Peter Dayan; Eric Schulz (CoRR, 2024)

Simplicity in Complexity. - Kevin Shen; Surabhi S. Nath; Aenne Brielmann; Peter Dayan (CoRR, 2024)

Detecting and Deterring Manipulation in a Cognitive Hierarchy. - Nitay Alon; Lion Schulz; Joseph M. Barnby; Jeffrey S. Rosenschein; Peter Dayan (CoRR, 2024)

Next state prediction gives rise to entangled, yet compositional representations of objects. - Tankred Saanum; Luca M. Schulze Buschoff; Peter Dayan; Eric Schulz (CoRR, 2024)

Centaur: a foundation model of human cognition. - Marcel Binz; Elif Akata; Matthias Bethge; Franziska Brändle; Fred Callaway; Julian Coda-Forno; Peter Dayan; Can Demircan; Maria K. Eckstein; Noémi Élteto; Thomas L. Griffiths 001; Susanne Haridi; et al. (CoRR, 2024)

Wagers for work: Decomposing the costs of cognitive effort. - Sarah L. Master; Clayton E. Curtis; Peter Dayan (PLoS Comput. Biol., 2024)

Code: Exploring replay. - Georgy Antonov; Peter Dayan (Zenodo, 2024)

Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. - Shuchen Wu; Mirko Thalmann; Peter Dayan; Zeynep Akata; Eric Schulz (ICLR, 2025)

Noradrenergic and Dopaminergic modulation of meta-cognition and meta-control. - Sara Ershadmanesh; Sahar Rajabi; Reza Rostami; Rani Moran; Peter Dayan (PLoS Comput. Biol., 2025)

A Data-Centric Approach: Dimensions of Visual Complexity and How to find Them. - Karahan Saritas; Tingke Shen; Surabhi S. Nath; Peter Dayan (CoRR, 2025)

Behavioural data, Bayesian Priors in Active Avoidance. - Tobias Granwald; Peter Dayan; Máté Lengyel; Marc Guitart-Masip (Zenodo, 2025)

Concept-Guided Interpretability via Neural Chunking. - Shuchen Wu; Stephan Alaniz; Shyamgopal Karthik; Peter S. Dayan; Eric Schulz; Zeynep Akata (CoRR, 2025)

Analogy making as amortised model construction. - David G. Nagy; Tingke Shen; Hanqi Zhou; Charley M. Wu; Peter Dayan (CoRR, 2025)

A foundation model to predict and capture human cognition. - Marcel Binz; Elif Akata; Matthias Bethge; Franziska Brändle; Fred Callaway; Julian Coda-Forno; Peter Dayan; Can Demircan; Maria K. Eckstein; Noémi Élteto; Thomas L. Griffiths 001; Susanne Haridi; et al. (Nat., 2025)