Supervised learning algorithms can train neural units and networks to estimate probabilities and simulate the responses of neurons to multisensory stimulation
9.1 Implementing a Simple Classifier as a Three-Layered Neural Network
9.2 Predicting Rain as an Everyday Example of Probabilistic Inference
9.3 Implementing a Simple Classifier Using Bayes' Rule
9.4 Modeling Neural Responses to Sensory Input as a Probabilistic Inference
9.5 Modeling Multisensory Collicular Neurons as Probability Estimators
9.9.Simulating the Development of Non-Uniform Distributed Representations
9.7 Modeling Non-Uniform Distributed Representations in the Vestibular Nuclei
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Researchers should cite this work as follows:
University of Illinois at Urbana-Champaign, Urbana, IL
University of Illinois at Urbana-Champaign
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