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Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models

Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models

This video was recorded at Video Journal of Machine Learning Abstracts - Volume 3. Recent experiments have demonstrated that humans and animals typically reason probabilistically about their environment. This ability requires a neural code that represents probability distributions and neural circuits that are capable of implementing the operations of probabilistic inference. The proposed probabilistic population coding (PPC) framework provides a statistically efficient neural representation of probability distributions that is both broadly consistent with physiological measurements and capable of implementing some of the basic operations of probabilistic inference in a biologically plausible way. However, these experiments and the corresponding neural models have largely focused on simple... Show More
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