CPC G06N 3/044 (2023.01) [G06N 3/08 (2013.01)] | 23 Claims |
1. A device comprising:
a neural network implemented in a data processing apparatus and trained to produce:
in response to a first input, a first representation of presence or absence of each of a plurality of individual topological patterns of signal transmission activity that would arise between nodes along links in a source recurrent neural network in response to the first input, wherein
the source recurrent neural network differs from the neural network,
the first representation only approximates the presence or the absence of each of the individual topological patterns of signal transmission activity that would arise in the source recurrent neural network in response to the first input, and
the first representation does not encode locations of the nodes and the links in a graph of the source recurrent neural network;
in response to a second input, a second representation of presence or absence of each of the plurality of the individual topological patterns of signal transmission activity that would arise between the nodes along the links in the source recurrent neural network in response to the second input, wherein the second representation only approximates the presence or the absence of each of the individual topological patterns of signal transmission activity that would arise in the source recurrent neural network in response to the second input and the second representation does not encode locations of the nodes and the links in the graph of the source recurrent neural network; and
in response to a third input, a third representation of presence or absence of each of the plurality of the individual topological patterns of signal transmission activity that would arise between the nodes along the links in the source recurrent neural network in response to the third input, wherein the third representation only approximates the presence or the absence of each of the individual topological patterns of signal transmission activity that would arise in the source recurrent neural network in response to the third input and the second representation does not encode locations of the nodes and the links in the graph of the source recurrent neural network.
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