SELECTING NEURAL NETWORK ARCHITECTURES BASED ON COMMUNITY GRAPHS
Abstract:
In one aspect, there is provided a method performed by one or more data processing apparatus, the method including: obtaining data defining a connectivity graph that represents synaptic connectivity between multiple biological neuronal elements in a brain of a biological organism, where the connectivity graph includes: multiple nodes, and multiple edges that each connect a respective pair of nodes, determining a partition of the connectivity graph into multiple community sub-graphs by performing an optimization that encourages a higher measure of connectedness between nodes included within each community sub-graph relative to nodes included in different community sub-graphs, and selecting a neural network architecture for performing a machine learning task using multiple community sub-graphs determined by the optimization that encourages the higher measure of connectedness between nodes included within each community sub-graph relative to nodes included in different community sub-graphs.
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