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Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models
Published on Jan 14, 20133924 Views
Recent experiments have demonstrated that humans and animals typically reason probabilistically about their environment. This ability requires a neural code that represents probability distributions a
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Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models00:00
Linear Probabilistic Population Codes00:45
The Variational Bayesian Expectation Maximization algorithm naturally generates network dynamics that result in linear PPC’s02:01
Network implementations of inference and learning for spike train de-mixing with LDA and Dynamic LDA03:28