Peter Dayan - RankMe

197 papers A* 11A 1B 15C 2Journal 118Unranked 49

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Composing egocentric and allocentric maps for flexible navigation. PLoS Comput. Biol. Daniel Shani, Peter Dayan
2026	J	`jnl`	Homeostasis after injury: How intertwined inference and control underpin post-injury pain and behaviour. PLoS Comput. Biol. Pranav Mahajan, Peter Dayan, Ben Seymour
2026	J	`jnl`	Metacognitive efficiency in learned value-based choice. PLoS Comput. Biol. Sara Ershadmanesh, Ali Gholamzadeh, Kobe Desender, Peter Dayan
2026	J	`jnl`	ℵ-IPOMDP: Mitigating Deception in a Cognitive Hierarchy with Off-Policy Counterfactual Anomaly Detection. J. Artif. Intell. Res. Nitay Alon, Joseph M. Barnby, Stefan Sarkadi, Lion Schulz, Jeffrey S. Rosenschein, Peter Dayan
2025	J	`jnl`	A Data-Centric Approach: Dimensions of Visual Complexity and How to find Them. CoRR Karahan Saritas, Tingke Shen, Surabhi S. Nath, Peter Dayan
2025	J	`jnl`	A foundation model to predict and capture human cognition. Nat. 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, Susanne Haridi, Akshay K. Jagadish, Ji-An Li, Alexander Kipnis, Sreejan Kumar, Tobias Ludwig, Marvin Mathony, Marcelo G. Mattar, Alireza Modirshanechi, Surabhi S. Nath, Joshua C. Peterson, Milena Rmus, Evan M. Russek, Tankred Saanum, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert C. Wilson, Kristin Witte, Shuchen Wu, Dirk U. Wulff, Huadong Xiong, Eric Schulz
2025	J	`jnl`	Analogy making as amortised model construction. CoRR David G. Nagy, Tingke Shen, Hanqi Zhou, Charley M. Wu, Peter Dayan
2025	A*	`conf`	Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. ICLR Shuchen Wu, Mirko Thalmann, Peter Dayan, Zeynep Akata, Eric Schulz
2025	B	`conf`	Complexity in Complexity: Understanding Visual Complexity Through Structure, Color, and Surprise. CogSci Karahan Saritas, Peter Dayan, Tingke Shen, Surabhi S. Nath
2025	J	`jnl`	Mechanisms of mistrust: A Bayesian account of misinformation learning. PLoS Comput. Biol. Lion Schulz, Yannick Streicher, Eric Schulz, Rahul Bhui, Peter Dayan
2025	J	`jnl`	Noradrenergic and Dopaminergic modulation of meta-cognition and meta-control. PLoS Comput. Biol. Sara Ershadmanesh, Sahar Rajabi, Reza Rostami, Rani Moran, Peter Dayan
2025	B	`conf`	Striking the Right Chord Between Reuse and Improvisation: Melody Learning as Resource-Rational Program Induction. CogSci Hanqi Zhou, David G. Nagy, Peter Dayan, Charley M. Wu
2024	J	`jnl`	Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. CoRR Shuchen Wu, Mirko Thalmann, Peter Dayan, Zeynep Akata, Eric Schulz
2024	J	`jnl`	Centaur: a foundation model of human cognition. CoRR 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, Susanne Haridi, Akshay K. Jagadish, Ji-An Li, Alexander Kipnis, Sreejan Kumar, Tobias Ludwig, Marvin Mathony, Marcelo G. Mattar, Alireza Modirshanechi, Surabhi S. Nath, Joshua C. Peterson, Milena Rmus, Evan M. Russek, Tankred Saanum, Natalia Scharfenberg, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert C. Wilson, Kristin Witte, Shuchen Wu, Dirk U. Wulff, Huadong Xiong, Eric Schulz
2024	C	`conf`	Characterising the Creative Process in Humans and Large Language Models. ICCC Surabhi S. Nath, Peter Dayan, Claire E. Stevenson
2024	J	`jnl`	Characterising the Creative Process in Humans and Large Language Models. CoRR Surabhi S. Nath, Peter Dayan, Claire E. Stevenson
2024	J	`jnl`	Detecting and Deterring Manipulation in a Cognitive Hierarchy. CoRR Nitay Alon, Lion Schulz, Joseph M. Barnby, Jeffrey S. Rosenschein, Peter Dayan
2024	J	`jnl`	Exploring Uncertainty in Distributional Reinforcement Learning. RLJ Georgy Antonov, Peter Dayan
2024	J	`jnl`	Next state prediction gives rise to entangled, yet compositional representations of objects. CoRR Tankred Saanum, Luca M. Schulze Buschoff, Peter Dayan, Eric Schulz
2024	B	`conf`	Optimal and sub-optimal temporal decisions can explain procrastination in a real-world task. CogSci Sahiti Chebolu, Peter Dayan
2024	J	`jnl`	Predicting the Future with Simple World Models. CoRR Tankred Saanum, Peter Dayan, Eric Schulz
2024	J	`jnl`	Simplicity in Complexity. CoRR Kevin Shen, Surabhi S. Nath, Aenne Brielmann, Peter Dayan
2024	B	`conf`	Simplicity in Complexity: Explaining Visual Complexity using Deep Segmentation Models. CogSci Tingke Shen, Surabhi S. Nath, Aenne Brielmann, Peter Dayan
2024	A*	`conf`	Simplifying Latent Dynamics with Softly State-Invariant World Models. NeurIPS Tankred Saanum, Peter Dayan, Eric Schulz
2024	B	`conf`	State-Independent and State-Dependent Learning in a Motivational Go/NoGo task. CogSci Azadeh Nazemorroaya, Dan Bang, Peter Dayan
2024	J	`jnl`	Wagers for work: Decomposing the costs of cognitive effort. PLoS Comput. Biol. Sarah L. Master, Clayton E. Curtis, Peter Dayan
2023	B	`conf`	Compositionality under time pressure. CogSci Valerio Rubino, Mani Hamidi, Peter Dayan, Charley M. Wu
2023	B	`conf`	Habits of Mind: Reusing Action Sequences for Efficient Planning. CogSci Noémi Élteto, Peter Dayan
2023	J	`jnl`	Habits of Mind: Reusing Action Sequences for Efficient Planning. CoRR Noémi Élteto, Peter Dayan
2023	J	`jnl`	Reframing dopamine: A controlled controller at the limbic-motor interface. PLoS Comput. Biol. Kevin Lloyd, Peter Dayan
2023	A*	`conf`	Reinforcement Learning with Simple Sequence Priors. NeurIPS Tankred Saanum, Noémi Élteto, Peter Dayan, Marcel Binz, Eric Schulz
2023	J	`jnl`	Reinforcement Learning with Simple Sequence Priors. CoRR Tankred Saanum, Noémi Élteto, Peter Dayan, Marcel Binz, Eric Schulz
2023	J	`jnl`	The Inner Sentiments of a Thought. CoRR Chris Gagne, Peter Dayan
2022	J	`jnl`	Biased belief priors versus biased belief updating: Differential correlates of depression and anxiety. PLoS Comput. Biol. Christopher Gagne, Sharon Agai, Christian Ramiro, Peter Dayan, Sonia J. Bishop
2022	J	`jnl`	Interactions between attributions and beliefs at trial-by-trial level: Evidence from a novel computer game task. PLoS Comput. Biol. Elena Zamfir, Peter Dayan
2022	A*	`conf`	Neural Network Poisson Models for Behavioural and Neural Spike Train Data. ICML Moein Khajehnejad, Forough Habibollahi, Richard Nock, Ehsan Arabzadeh, Peter Dayan, Amir Dezfouli
2022	J	`jnl`	Optimism and pessimism in optimised replay. PLoS Comput. Biol. Georgy Antonov, Christopher Gagne, Eran Eldar, Peter Dayan
2022	J	`jnl`	The pursuit of happiness: A reinforcement learning perspective on habituation and comparisons. PLoS Comput. Biol. Rachit Dubey, Thomas L. Griffiths, Peter Dayan
2022	J	`jnl`	Tracking human skill learning with a hierarchical Bayesian sequence model. PLoS Comput. Biol. Noémi Élteto, Dezso Németh, Karolina Janacsek, Peter Dayan
2022	J	`jnl`	Vigilance, arousal, and acetylcholine: Optimal control of attention in a simple detection task. PLoS Comput. Biol. Sahiti Chebolu, Peter Dayan, Kevin Lloyd
2021	J	`jnl`	Catastrophe, Compounding & Consistency in Choice. CoRR Chris Gagne, Peter Dayan
2021	B	`conf`	Confidence in control: Metacognitive computations for information search. CogSci Lion Schulz, Stephen M. Fleming, Peter Dayan
2021	A*	`conf`	Correcting experience replay for multi-agent communication. ICLR Sanjeevan Ahilan, Peter Dayan
2021	J	`jnl`	Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach. PLoS Comput. Biol. Vikki Neville, Peter Dayan, Iain D. Gilchrist, Elizabeth S. Paul, Michael Mendl
2021	B	`conf`	Exploring learning trajectories with dynamic infinite hidden Markov models. CogSci Sebastian A. Bruijns, International Brain Laboratory, Peter Dayan
2021	J	`jnl`	Internality and the internalisation of failure: Evidence from a novel task. PLoS Comput. Biol. Federico Mancinelli, Jonathan P. Roiser, Peter Dayan
2021	B	`conf`	Tracking the Unknown: Modeling Long-Term Implicit Skill Acquisition as Non-Parametric Bayesian Sequence Learning. CogSci Noémi Élteto, Dezso Németh, Karolina Janacsek, Peter Dayan
2021	A*	`conf`	Two steps to risk sensitivity. NeurIPS Chris Gagne, Peter Dayan
2021	J	`jnl`	Two steps to risk sensitivity. CoRR Chris Gagne, Peter Dayan
2021	J	`jnl`	Using Primary Reinforcement to Enhance Translatability of a Human Affect and Decision-Making Judgment Bias Task. J. Cogn. Neurosci. Vikki Neville, Peter Dayan, Iain D. Gilchrist, Elizabeth S. Paul, Michael Mendl
2020	A*	`conf`	A Local Temporal Difference Code for Distributional Reinforcement Learning. NeurIPS Pablo Tano, Peter Dayan, Alexandre Pouget
2020	J	`jnl`	Combined model-free and model-sensitive reinforcement learning in non-human primates. PLoS Comput. Biol. Bruno Miranda, W. M. Nishantha Malalasekera, Timothy Edward John Behrens, Peter Dayan, Steven W. Kennerley
2020	J	`jnl`	Correcting Experience Replay for Multi-Agent Communication. CoRR Sanjeevan Ahilan, Peter Dayan
2020	A	`conf`	Static and Dynamic Values of Computation in MCTS. UAI Eren Sezener, Peter Dayan
2020	J	`jnl`	Static and Dynamic Values of Computation in MCTS. CoRR Eren Sezener, Peter Dayan
2019	J	`jnl`	A computational account of threat-related attentional bias. PLoS Comput. Biol. Toby Wise, Jochen Michely, Peter Dayan, Raymond J. Dolan
2019	A*	`conf`	Disentangled behavioural representations. NeurIPS Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong
2019	J	`jnl`	Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning. CoRR Sanjeevan Ahilan, Peter Dayan
2019	J	`jnl`	Learning to use past evidence in a sophisticated world model. PLoS Comput. Biol. Sanjeevan Ahilan, Rebecca B. Solomon, Yannick-André Breton, Kent L. Conover, Ritwik K. Niyogi, Peter Shizgal, Peter Dayan
2019	J	`jnl`	Models that learn how humans learn: The case of decision-making and its disorders. PLoS Comput. Biol. Amir Dezfouli, Kristi Griffiths, Fabio Ramos, Peter Dayan, Bernard W. Balleine
2018	J	`jnl`	A model of risk and mental state shifts during social interaction. PLoS Comput. Biol. Andreas Hula, Iris Vilares, Terry Lohrenz, Peter Dayan, P. Read Montague
2018	J	`jnl`	Applying the RE-AIM Framework for the Evaluation of a Clinical Decision Support Tool for Pediatric Head Trauma: A Mixed-Methods Study. Appl. Clin. Inform. Ruth Masterson Creber, Peter Dayan, Nathan Kuppermann, Dustin W. Ballard, Leah Tzimenatos, Evaline Alessandrini, Rakesh Mistry, Jeffrey Hoffman, David R. Vinson, Suzanne Bakken
2018	J	`jnl`	Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood. PLoS Comput. Biol. Michael Moutoussis, Edward T. Bullmore, Ian M. Goodyer, Peter Fonagy, Peter B. Jones, Raymond J. Dolan, Peter Dayan
2018	J	`jnl`	Control of neurite growth and guidance by an inhibitory cell-body signal. PLoS Comput. Biol. Brendan A. Bicknell, Zac Pujic, Peter Dayan, Geoffrey J. Goodhill
2018	J	`jnl`	Examining Workflow in a Pediatric Emergency Department to Develop a Clinical Decision Support for an Antimicrobial Stewardship Program. Appl. Clin. Inform. Mustafa Ozkaynak, Danny Wu, Katia Hannah, Peter Dayan, Rakesh Mistry
2018	A*	`conf`	Fast Parametric Learning with Activation Memorization. ICML Jack W. Rae, Chris Dyer, Peter Dayan, Timothy P. Lillicrap
2018	J	`jnl`	Fast Parametric Learning with Activation Memorization. CoRR Jack W. Rae, Chris Dyer, Peter Dayan, Timothy P. Lillicrap
2018	A*	`conf`	Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models. NeurIPS Amir Dezfouli, Richard W. Morris, Fabio T. Ramos, Peter Dayan, Bernard W. Balleine
2018	J	`jnl`	Interrupting behaviour: Minimizing decision costs via temporal commitment and low-level interrupts. PLoS Comput. Biol. Kevin Lloyd, Peter Dayan
2018	J	`jnl`	Learning Contextual Reward Expectations for Value Adaptation. J. Cogn. Neurosci. Francesco Rigoli, Benjamin Chew, Peter Dayan, Raymond J. Dolan
2018	J	`jnl`	Probabilistic Meta-Representations Of Neural Networks. CoRR Theofanis Karaletsos, Peter Dayan, Zoubin Ghahramani
2017	B	`conf`	A model of structure learning, inference, and generation for scene understanding. CogSci David Raposo, Peter Dayan, Demis Hassabis, Peter W. Battaglia
2017	J	`jnl`	Comparison of Maximum Likelihood and GAN-based training of Real NVPs. CoRR Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria, Daan Wierstra, Peter Dayan
2017	J	`jnl`	Increased decision thresholds enhance information gathering performance in juvenile Obsessive-Compulsive Disorder (OCD). PLoS Comput. Biol. Tobias U. Hauser, Michael Moutoussis, Reto Iannaccone, Silvia Brem, Susanne Walitza, Renate Drechsler, Peter Dayan, Raymond J. Dolan
2016	J	`jnl`	Clinical Decision Support for a Multicenter Trial of Pediatric Head Trauma. Appl. Clin. Inform. 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, Peter Dayan, Eric Tham
2016	J	`jnl`	Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning. CoRR Neil R. Bramley, Peter Dayan, Thomas L. Griffiths, David A. Lagnado
2016	J	`jnl`	How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences. PLoS Comput. Biol. Michael Moutoussis, Raymond J. Dolan, Peter Dayan
2016	J	`jnl`	Multiple value signals in dopaminergic midbrain and their role in avoidance contexts. NeuroImage Francesco Rigoli, Benjamin Chew, Peter Dayan, Raymond J. Dolan
2016	J	`jnl`	The Dopaminergic Midbrain Mediates an Effect of Average Reward on Pavlovian Vigor. J. Cogn. Neurosci. Francesco Rigoli, Benjamin Chew, Peter Dayan, Raymond J. Dolan
2016	J	`jnl`	The influence of contextual reward statistics on risk preference. NeuroImage Francesco Rigoli, Robb B. Rutledge, Peter Dayan, Raymond J. Dolan
2015	J	`jnl`	A Probabilistic Palimpsest Model of Visual Short-term Memory. PLoS Comput. Biol. Loic Matthey, Paul M. Bays, Peter Dayan
2015	J	`jnl`	Anticipation and Choice Heuristics in the Dynamic Consumption of Pain Relief. PLoS Comput. Biol. Giles W. Story, Ivo Vlaev, Peter Dayan, Ben Seymour, Ara Darzi, Raymond J. Dolan
2015	J	`jnl`	Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange. PLoS Comput. Biol. Andreas Hula, P. Read Montague, Peter Dayan
2015	J	`jnl`	Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task. PLoS Comput. Biol. Thomas E. Akam, Rui Costa, Peter Dayan
2015	B	`conf`	Staying afloat on Neurath's boat - Heuristics for sequential causal learning. CogSci Neil Bramley, Peter Dayan, David A. Lagnado
2015	J	`jnl`	Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens. PLoS Comput. Biol. Kevin Lloyd, Peter Dayan
2014	—	`conf`	Bayes-Adaptive Simulation-based Search with Value Function Approximation. NIPS Arthur Guez, Nicolas Heess, David Silver, Peter Dayan
2014	J	`jnl`	Better Optimism By Bayes: Adaptive Planning with Rich Models. CoRR Arthur Guez, David Silver, Peter Dayan
2014	J	`jnl`	Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3. PLoS Comput. Biol. Cristina Savin, Peter Dayan, Máté Lengyel
2014	J	`jnl`	Rationalizable Irrationalities of Choice. Top. Cogn. Sci. Peter Dayan
2014	J	`jnl`	Some Work and Some Play: Microscopic and Macroscopic Approaches to Labor and Leisure. PLoS Comput. Biol. Ritwik K. Niyogi, Peter Shizgal, Peter Dayan
2013	—	`conf`	Correlations strike back (again): the case of associative memory retrieval. NIPS Cristina Savin, Peter Dayan, Máté Lengyel
2013	—	`ch.`	Exploration from Generalization Mediated by Multiple Controllers. Intrinsically Motivated Learning in Natural and Artificial Systems Peter Dayan
2013	J	`jnl`	Scalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search. J. Artif. Intell. Res. Arthur Guez, David Silver, Peter Dayan
2013	J	`jnl`	Sparse Coding Can Predict Primary Visual Cortex Receptive Field Changes Induced by Abnormal Visual Input. PLoS Comput. Biol. Jonathan J. Hunt, Peter Dayan, Geoffrey J. Goodhill
2013	B	`conf`	Structured cognitive representations and complex inference in neural systems. CogSci Samuel Gershman, Joshua B. Tenenbaum, Alexandre Pouget, Matthew M. Botvinick, Peter Dayan
2012	J	`jnl`	Bonsai Trees in Your Head: How the Pavlovian System Sculpts Goal-Directed Choices by Pruning Decision Trees. PLoS Comput. Biol. Quentin J. M. Huys, Neir Eshel, Elizabeth J. P. O'Nions, Luke Sheridan, Peter Dayan, Jonathan P. Roiser
2012	J	`jnl`	Computational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thought. PLoS Comput. Biol. Ting Xiang, Debajyoti Ray, Terry Lohrenz, Peter Dayan, P. Read Montague
2012	B	`conf`	Computational, Cognitive, and Neural Models of Decision-making Biases. CogSci Jonathan Malmaud, Joshua B. Tenenbaum, Peter Dayan, Laurence T. Maloney, Edward Vul, Nick Chater
2012	J	`jnl`	Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics. PLoS Comput. Biol. Ruben Coen Cagli, Peter Dayan, Odelia Schwartz
2012	B	`conf`	Dynamic decision making: neuronal, computational, and cognitive underpinnings. CogSci Magda Osman, Maarten Speekenbrink, Peter Dayan, Masataka Watanabe, Nigel Harvey
2012	J	`jnl`	Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search CoRR Arthur Guez, David Silver, Peter Dayan
2012	—	`conf`	Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. NIPS Arthur Guez, David Silver, Peter Dayan
2012	J	`jnl`	Go and no-go learning in reward and punishment: Interactions between affect and effect. NeuroImage Marc Guitart-Masip, Quentin J. M. Huys, Lluís Fuentemilla, Peter Dayan, Emrah Düzel, Raymond J. Dolan
2011	J	`jnl`	Bayes-Optimal Chemotaxis. Neural Comput. Duncan Mortimer, Peter Dayan, Kevin Burrage, Geoffrey J. Goodhill
2011	J	`jnl`	Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding. PLoS Comput. Biol. Quentin J. M. Huys, Roshan Cools, Martin Gölzer, Eva Friedel, Andreas Heinz, Raymond J. Dolan, Peter Dayan
2011	J	`jnl`	Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131). Dagstuhl Reports Jeremy L. Wyatt, Peter Dayan, Ales Leonardis, Jan Peters
2011	—	`conf`	Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories. NIPS Cristina Savin, Peter Dayan, Máté Lengyel
2011	J	`jnl`	Vigor in the Face of Fluctuating Rates of Reward: An Experimental Examination. J. Cogn. Neurosci. Marc Guitart-Masip, Ulrik R. Beierholm, Raymond J. Dolan, Emrah Düzel, Peter Dayan
2010	J	`jnl`	Change-Based Inference in Attractor Nets: Linear Analysis. Neural Comput. Reza Moazzezi, Peter Dayan
2010	J	`jnl`	Pavlovian-Instrumental Interaction in 'Observing Behavior'. PLoS Comput. Biol. Ulrik R. Beierholm, Peter Dayan
2009	J	`jnl`	Goal-directed control and its antipodes. Neural Networks Peter Dayan
2009	—	`conf`	Know Thy Neighbour: A Normative Theory of Synaptic Depression. NIPS Jean-Pascal Pfister, Peter Dayan, Máté Lengyel
2009	—	`conf`	Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing. NIPS Ruben Coen Cagli, Peter Dayan, Odelia Schwartz
2008	J	`jnl`	A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis. Medical Biol. Eng. Comput. Marzia De Lucia, Juan Fritschy, Peter Dayan, David S. Holder
2008	—	`conf`	Bayesian Model of Behaviour in Economic Games. NIPS Debajyoti Ray, Brooks King-Casas, P. Read Montague, Peter Dayan
2008	J	`jnl`	Encoding and Decoding Spikes for Dynamic Stimuli. Neural Comput. Rama Natarajan, Quentin J. M. Huys, Peter Dayan, Richard S. Zemel
2008	—	`conf`	Load and Attentional Bayes. NIPS Peter Dayan
2008	—	`conf`	Psychiatry: Insights into depression through normative decision-making models. NIPS Quentin J. M. Huys, Joshua T. Vogelstein, Peter Dayan
2008	J	`jnl`	Serotonin, Inhibition, and Negative Mood. PLoS Comput. Biol. Peter Dayan, Quentin J. M. Huys
2007	J	`jnl`	Bilinearity, rules, and prefrontal cortex. Frontiers Comput. Neurosci. Peter Dayan
2007	J	`jnl`	Fast Population Coding. Neural Comput. Quentin J. M. Huys, Richard S. Zemel, Rama Natarajan, Peter Dayan
2007	—	`conf`	Hippocampal Contributions to Control: The Third Way. NIPS Máté Lengyel, Peter Dayan
2006	J	`jnl`	Dopamine modulation in the basal ganglia locks the gate to working memory. J. Comput. Neurosci. Aaron J. Gruber, Peter Dayan, Boris S. Gutkin, Sara A. Solla
2006	J	`jnl`	Images, Frames, and Connectionist Hierarchies. Neural Comput. Peter Dayan
2006	J	`jnl`	Pre-attentive visual selection. Neural Networks Zhaoping Li, Peter Dayan
2006	J	`jnl`	Soft Mixer Assignment in a Hierarchical Generative Model of Natural Scene Statistics. Neural Comput. Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan
2006	J	`jnl`	The misbehavior of value and the discipline of the will. Neural Networks Peter Dayan, Yael Niv, Ben Seymour, Nathaniel D. Daw
2006	—	`conf`	Uncertainty, phase and oscillatory hippocampal recall. NIPS Máté Lengyel, Peter Dayan
2005	—	`conf`	A Bayesian Framework for Tilt Perception and Confidence. NIPS Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan
2005	C	`conf`	Differential Priors for Elastic Nets. IDEAL Miguel Á. Carreira-Perpiñán, Peter Dayan, Geoffrey J. Goodhill
2005	—	`conf`	How fast to work: Response vigor, motivation and tonic dopamine. NIPS Yael Niv, Nathaniel D. Daw, Peter Dayan
2005	—	`conf`	Norepinephrine and Neural Interrupts. NIPS Peter Dayan, Angela J. Yu
2004	—	`conf`	Assignment of Multiplicative Mixtures in Natural Images. NIPS Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan
2004	—	`conf`	Inference, Attention, and Decision in a Bayesian Neural Architecture. NIPS Angela J. Yu, Peter Dayan
2004	—	`conf`	Probabilistic Computation in Spiking Populations. NIPS Richard S. Zemel, Quentin J. M. Huys, Rama Natarajan, Peter Dayan
2004	—	`conf`	Rate- and Phase-coded Autoassociative Memory. NIPS Máté Lengyel, Peter Dayan
2003	—	`conf`	Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory. NIPS Aaron J. Gruber, Peter Dayan, Boris S. Gutkin, Sara A. Solla
2003	J	`jnl`	Doubly Distributional Population Codes: Simultaneous Representation of Uncertainty and Multiplicity. Neural Comput. Maneesh Sahani, Peter Dayan
2003	—	`conf`	Plasticity Kernels and Temporal Statistics. NIPS Peter Dayan, Michael Häusser
2002	J	`jnl`	Acetylcholine in cortical inference. Neural Networks Angela J. Yu, Peter Dayan
2002	—	`conf`	Adaptation and Unsupervised Learning. NIPS Peter Dayan, Maneesh Sahani, Gregoire Deback
2002	J	`jnl`	Dopamine: generalization and bonuses. Neural Networks Sham M. Kakade, Peter Dayan
2002	—	`conf`	Expected and Unexpected Uncertainty: ACh and NE in the Neocortex. NIPS Angela J. Yu, Peter Dayan
2002	J	`jnl`	Introduction for 2002 Special Issue: Computational Models of Neuromodulation. Neural Networks Kenji Doya, Peter Dayan, Michael E. Hasselmo
2002	J	`jnl`	Opponent interactions between serotonin and dopamine. Neural Networks Nathaniel D. Daw, Sham M. Kakade, Peter Dayan
2002	—	`conf`	Replay, Repair and Consolidation. NIPS Szabolcs Káli, Peter Dayan
2002	J	`jnl`	Structure in the Space of Value Functions. Mach. Learn. David J. Foster, Peter Dayan
2001	J	`jnl`	A familiarity-based learning procedure for the establishment of place fields in area CA3 of the rat hippocampus. Neurocomputing Szabolcs Káli, Peter Dayan
2001	—	`conf`	ACh, Uncertainty, and Cortical Inference. NIPS Peter Dayan, Angela J. Yu
2001	—	`conf`	Motivated Reinforcement Learning. NIPS Peter Dayan
2000	—	`conf`	Competition and Arbors in Ocular Dominance. NIPS Peter Dayan
2000	—	`conf`	Dopamine Bonuses. NIPS Sham M. Kakade, Peter Dayan
2000	—	`conf`	Explaining Away in Weight Space. NIPS Peter Dayan, Sham M. Kakade
2000	—	`conf`	Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex. NIPS Szabolcs Káli, Peter Dayan
2000	—	`conf`	Position Variance, Recurrence and Perceptual Learning. NIPS Zhaoping Li, Peter Dayan
1999	—	`conf`	Acquisition in Autoshaping. NIPS Sham M. Kakade, Peter Dayan
1999	J	`jnl`	Recurrent Sampling Models for the Helmholtz Machine. Neural Comput. Peter Dayan
1999	J	`jnl`	The Effect of Correlated Variability on the Accuracy of a Population Code. Neural Comput. L. F. Abbott, Peter Dayan
1998	J	`jnl`	A Hierarchical Model of Binocular Rivalry. Neural Comput. Peter Dayan
1998	J	`jnl`	Analytical Mean Squared Error Curves for Temporal Difference Learning. Mach. Learn. Satinder Singh, Peter Dayan
1998	J	`jnl`	Bayesian retrieval in associative memories with storage errors. IEEE Trans. Neural Networks Friedrich T. Sommer, Peter Dayan
1998	—	`conf`	Computational Differences between Asymmetrical and Symmetrical Networks. NIPS Zhaoping Li, Peter Dayan
1998	—	`conf`	Distributional Population Codes and Multiple Motion Models. NIPS Richard S. Zemel, Peter Dayan
1998	J	`jnl`	Probabilistic Interpretation of Population Codes. Neural Comput. Richard S. Zemel, Peter Dayan, Alexandre Pouget
1997	—	`conf`	Combining Probabilistic Population Codes. IJCAI Richard S. Zemel, Peter Dayan
1997	J	`jnl`	Factor Analysis Using Delta-Rule Wake-Sleep Learning. Neural Comput. Radford M. Neal, Peter Dayan
1997	—	`conf`	Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning. NIPS David J. Foster, Richard G. M. Morris, Peter Dayan
1997	J	`jnl`	Modeling the manifolds of images of handwritten digits. IEEE Trans. Neural Networks Geoffrey E. Hinton, Peter Dayan, Michael Revow
1997	—	`conf`	Statistical Models of Conditioning. NIPS Peter Dayan, Theresa Long
1997	J	`jnl`	Using Expectation-Maximization for Reinforcement Learning. Neural Comput. Peter Dayan, Geoffrey E. Hinton
1996	—	`conf`	A Hierarchical Model of Visual Rivalry. NIPS Peter Dayan
1996	—	`conf`	Analytical Mean Squared Error Curves in Temporal Difference Learning. NIPS Satinder Singh, Peter Dayan
1996	J	`jnl`	Exploration Bonuses and Dual Control. Mach. Learn. Peter Dayan, Terrence J. Sejnowski
1996	—	`conf`	Neural Models for Part-Whole Hierarchies. NIPS Maximilian Riesenhuber, Peter Dayan
1996	—	`conf`	Probabilistic Interpretation of Population Codes. NIPS Richard S. Zemel, Peter Dayan, Alexandre Pouget
1996	J	`jnl`	Varieties of Helmholtz Machine. Neural Networks Peter Dayan, Geoffrey E. Hinton
1995	J	`jnl`	Competition and Multiple Cause Models. Neural Comput. Peter Dayan, Richard S. Zemel
1995	—	`conf`	Does the Wake-sleep Algorithm Produce Good Density Estimators? NIPS Brendan J. Frey, Geoffrey E. Hinton, Peter Dayan
1995	—	`conf`	Improving Policies without Measuring Merits. NIPS Peter Dayan, Satinder Singh
1995	A*	`conf`	Predictive Hebbian Learning. COLT Terrence J. Sejnowski, Peter Dayan, P. Read Montague
1995	J	`jnl`	The Helmholtz machine. Neural Comput. Peter Dayan, Geoffrey E. Hinton, Radford M. Neal, Richard S. Zemel
1994	—	`conf`	Recognizing Handwritten Digits Using Mixtures of Linear Models. NIPS Geoffrey E. Hinton, Michael Revow, Peter Dayan
1994	J	`jnl`	TD(lambda) Converges with Probability 1. Mach. Learn. Peter Dayan, Terrence J. Sejnowski
1993	J	`jnl`	Arbitrary Elastic Topologies and Ocular Dominance. Neural Comput. Peter Dayan
1993	—	`conf`	Foraging in an Uncertain Environment Using Predictive Hebbian Learning. NIPS P. Read Montague, Peter Dayan, Terrence J. Sejnowski
1993	J	`jnl`	Improving Generalization for Temporal Difference Learning: The Successor Representation. Neural Comput. Peter Dayan
1993	—	`conf`	Temporal Difference Learning of Position Evaluation in the Game of Go. NIPS Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski
1993	J	`jnl`	The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. Neural Comput. Peter Dayan, Terrence J. Sejnowski
1992	—	`conf`	Feudal Reinforcement Learning. NIPS Peter Dayan, Geoffrey E. Hinton
1992	J	`jnl`	Technical Note Q-Learning. Mach. Learn. Christopher J. C. H. Watkins, Peter Dayan
1992	J	`jnl`	The Convergence of TD(lambda) for General lambda. Mach. Learn. Peter Dayan
1992	—	`conf`	Using Aperiodic Reinforcement for Directed Self-Organization During Development. NIPS P. Read Montague, Peter Dayan, Steven J. Nowlan, Terrence J. Sejnowski
1991	J	`jnl`	Optimising synaptic learning rules in linear associative memories. Biol. Cybern. Peter Dayan, David J. Willshaw
1991	—	`conf`	Perturbing Hebbian Rules. NIPS Peter Dayan, Geoffrey J. Goodhill
1990	—	`conf`	Navigating Through Temporal Difference. NIPS Peter Dayan
1990	J	`jnl`	Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down. Neural Comput. David J. Willshaw, Peter Dayan