Publikationen von P Dayan
Alle Typen
Preprint (39)
821.
Preprint
Low dimensional latent structure underlying the choices of mice. (eingereicht)
822.
Preprint
Comparative Computational Modeling of Approach-Avoidance Biases in Suicidal Populations via Hierarchical Bayesian Inference. (eingereicht)
823.
Preprint
Risking your Tail: Curiosity, Danger and Exploration. (eingereicht)
824.
Preprint
An integrative framework for the human sense of control. (eingereicht)
825.
Preprint
Absence of Systematic Effects of Internalizing Psychopathology on Learning Under Uncertainty. (eingereicht)
826.
Preprint
A decision-theoretic model of perceptual multistability: perceptual switches as internal actions. (eingereicht)
827.
Preprint
A Data-Centric Approach: Dimensions of Visual Complexity and How to find Them. (eingereicht)
828.
Preprint
Weighting waiting: A decision-theoretic taxonomy of delay, pacing and procrastination. (eingereicht)
829.
Preprint
Distinct decision processes for 3D and motion stimuli in both humans and monkeys revealed by computational modelling. (eingereicht)
830.
Preprint
Bayesian Priors in Active Avoidance. (eingereicht)
831.
Preprint
Dissecting the Complexities of Learning With Infinite Hidden Markov Models. (eingereicht)
832.
Preprint
The Inner Sentiments of a Thought. (eingereicht)
833.
Preprint
Modeling individual aesthetic judgments over time. (eingereicht)
834.
Preprint
When it pays to be quick: dissociating control over task preparation and speed-accuracy trade-off in task switching. (eingereicht)
835.
Preprint
Subjective Beliefs In, Out, and About Control: A Quantitative Analysis. (eingereicht)
836.
Preprint
Hippocampal-midbrain circuit enhances the pleasure of anticipation in the prefrontal cortex. (eingereicht)
837.
Preprint
Phasic norepinephrine is a neural interrupt signal for unexpected events in rapidly unfolding sensory sequences: evidence from pupillometry. (eingereicht)
838.
Preprint
Comparison of Maximum Likelihood and GAN-based training of Real NVPs. (eingereicht)
839.
Preprint
Better Optimism By Bayes: Adaptive Planning with Rich Models. (eingereicht)