Explaining Away in Weight Space (2000)

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by Peter Dayan , Sham Kakade
Citations:14 - 2 self

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Explaining Away in Weight Space – Peter Dayan Sham, Peter Dayan, Sham Kakade
3 Semi-rational Models of Conditioning: The Case of Trial Order – Nathaniel D. Daw, Aaron C. Courville, Peter Dayan - 2007
18 The rat as particle filter – Nathaniel D. Daw, Aaron C. Courville, Université De Montréal
Surprising Predictions – n.n. - 1994
Centre single caption. cf. [no comma]. RJ OCR scanned – Klaus G. Melchers, Harald Lachnit, David R. Shanks
Animal Learning & Behavior – Nuria Ortega, Oskar Pineño
6 A comparison between elemental and compound training of cues in retrospective revaluation – Martha Escobar, Oskar Pineño, Helena Matute
3 Backward blocking: The role of within-compound . . . – Miguel A. Vadillo, Leyre Castro, Helena Matute, Edward A. Wasserman - 2008
Positive and negative mediation as a function of whether the absent cue was previously associated with the outcome – Leyre Castro, Helena Matute - 2010
Outcome similarity modulates retroactive interference . . . – Oskar Pineño, Helena Matute - 2005
95 A theory of causal learning in children: Causal maps and Bayes nets – Alison Gopnik, Clark Glymour, David M. Sobel, Laura E. Schulz, Tamar Kushnir, David Danks - 2004
16 Locally Bayesian Learning with Applications to Retrospective Revaluation and Highlighting – John K. Kruschke - 2006
1 Higher-order associative processing in hermissenda suggests multiple sites of neuronal modulation – R F Rogers, L D Matzel, Neuronal Modulation, Ronald F. Rogers, Louis D. Matzell - 1996
5 Timing and Partial Observability in the Dopamine System – Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky - 2003
18 Acquisition and extinction in autoshaping – Sham Kakade, Peter Dayan - 2002
Within-subjects Extinction and Renewal in Predictive Judgments – M. Concepción, M. Concepcion Paredes-Olay, Juan M. Rosas - 1999
18 Is there a geometric module for spatial orientation? Squaring theory and evidence – Ken Cheng, Nora S. Newcombe - 2005
Foraging Through Prediction – Peter Dayan, P Read Montague, Terrence J Sejnowski, P Read, Montague Terrence, J Sejnowski
Reinforcement Learning – Ar Ni Ng