Product forms in Neural Networks, G-Networks and Chemical Systems
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If you have a question about this talk, please contact Neil Walton.
We will review some of our work on product form networks, starting with a model of “excitation and inhibition” in spiked random neuronal ensembles. We will discuss learning and approximation in the context of the “random neural network”, followed by applications to image processing and network routing. We will then summarise extensions to product form G-networks, and also discuss recent results in chemical or population models, and models of networks of auctions.
This talk is part of the Optimization and Incentives Seminar series.
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