"An introduction to constructing and reasoning with Bayesian (probabilistic) models of perceptual decision making and action, modeling how the brain perceives and decides"--
"An introduction to constructing and reasoning with Bayesian (probabilistic) models of perceptual decision making and action, modeling how the brain perceives and decides"--
Wei Ji Ma, Konrad Paul Kording, and Daniel Goldreich
Inhaltsangabe
Acknowledgments xv The Four Steps of Bayesian Modeling xvii List of Acronyms xix Introduction 1 1 Uncertainty and Inference 7 2 Using Bayes' Rule 31 3 Bayesian Inference under Measurement Noise 53 4 The Response Distribution 83 5 Cue Combination and Evidence Accumulation 105 6 Learning as Inference 125 7 Discrimination and Detection 147 8 Binary Classification 169 9 Top-Level Nuisance Variables and Ambiguity 191 10 Same-Different Judgment 205 11 Search 227 12 Inference in a Changing World 245 13 Combining Inference with Utility 257 14 The Neural Likelihood Function 281 15 Bayesian Models in Context 301 Appendices 311 A Notation 313 B Basics of Probability Theory 315 C Model Fitting and Model Comparison 343 Bibliography 361 Index 371
Acknowledgments xv The Four Steps of Bayesian Modeling xvii List of Acronyms xix Introduction 1 1 Uncertainty and Inference 7 2 Using Bayes' Rule 31 3 Bayesian Inference under Measurement Noise 53 4 The Response Distribution 83 5 Cue Combination and Evidence Accumulation 105 6 Learning as Inference 125 7 Discrimination and Detection 147 8 Binary Classification 169 9 Top-Level Nuisance Variables and Ambiguity 191 10 Same-Different Judgment 205 11 Search 227 12 Inference in a Changing World 245 13 Combining Inference with Utility 257 14 The Neural Likelihood Function 281 15 Bayesian Models in Context 301 Appendices 311 A Notation 313 B Basics of Probability Theory 315 C Model Fitting and Model Comparison 343 Bibliography 361 Index 371
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