Kpnn2: sparsely connected PyTorch layers from a named graph, with attributions by node name

kpnn2 turns a graph of named entities into sparsely connected PyTorch layers. Each node becomes a unit, each edge becomes a weight, pairs without an edge stay unconnected, and attribution scores come back labeled by node name. You provide an edgelist and data with named features, and you train in ordinary PyTorch. From edgelist to layers import pandas as pd import kpnn2 edgelist = pd.DataFrame( [("input_signal_1", "hidden_signal"), ("input_signal_2", "hidden_signal"), ("input_nois...