Publikationen von P Dayan

Neal , R.; Dayan, P.: Factor Analysis Using Delta-Rule Wake-Sleep Learning. Neural computation 9 (8), S. 1781 - 1803 (1997)

Frey, B.; Dayan, P.; Hinton, G.: A simple algorithm that discovers efficient perceptual codes. Computational and Psychophysical Mechanisms of Visual Coding, S. 296 - 315 (1997)

Schultz, W.; Dayan, P.; Montague, P.: A neural substrate of prediction and reward. Science 275 (5306), S. 1593 - 1599 (1997)

Dayan, P.; Hinton, G.: Using Expectation-Maximization for Reinforcement Learning. Neural computation 9 (2), S. 271 - 278 (1997)

Hinton, G.; Dayan, P.; Revow, M.: Modeling the manifolds of images of handwritten digits. IEEE Transactions on Neural Networks 8 (1), S. 65 - 74 (1997)

Dayan, P.; Hinton, G.: Varieties of Helmholtz Machine. Neural networks 9 (8), S. 1385 - 1403 (1996)

Dayan, P.; Sejnowski, T.: Exploration bonuses and dual control. Machine Learning 25 (1), S. 5 - 22 (1996)

Montague, P.; Dayan, P.; Sejnowski, T.: A framework for mesencephalic dopamine systems based on predictive Hebbian learning. The Journal of Neuroscience 16 (5), S. 1936 - 1947 (1996)

Montague, P.; Dayan, P.; Person, C.; Sejnowski , T.: Bee foraging in uncertain environments using predictive hebbian learning. Nature 377 (6551), S. 725 - 728 (1995)

Dayan, P.; Hinton, G.; Neal, R.; Zemel, R.: The Helmholtz Machine. Neural computation 7 (5), S. 889 - 904 (1995)

Dayan, P.; Zemel, R.: Competition and Multiple Cause Models. Neural computation 7 (3), S. 565 - 579 (1995)

Hinton, G.; Dayan, P.; Frey, B.; Neal, R.: The "wake-sleep" algorithm for unsupervised neural networks. Science 268 (5214), S. 1158 - 1161 (1995)

Dayan, P.: Computational Modelling. Current Opinion in Neurobiology 4 (2), S. 212 - 217 (1994)

Dayan, P.; Sejnowski, T.: TD(λ) converges with probability 1. Machine Learning 14 (3), S. 295 - 301 (1994)

Berns, G.; Dayan, P.; Sejnowski, T.: A correlational model for the development of disparity selectivity in visual cortex that depends on prenatal and postnatal phases. Proceedings of the National Academy of Sciences of the United States of America 90 (17), S. 8277 - 8281 (1993)

Dayan, P.: Improving Generalization for Temporal Difference Learning: The Successor Representation. Neural computation 5 (4), S. 613 - 624 (1993)

Dayan, P.: Arbitrary Elastic Topologies and Ocular Dominance. Neural computation 5 (3), S. 392 - 401 (1993)

Dayan, P.; Sejnowski, T.: The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning. Neural computation 5 (2), S. 205 - 209 (1993)

Dayan, P.: The Convergence of TD(λ) for General λ. Machine Learning 8 (3-4), S. 341 - 362 (1992)

Watkins, C.; Dayan, P.: Q-learning. Machine Learning 8 (3-4), S. 279 - 292 (1992)