Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
from src.model.model_object_multiclass import ModelBuilder, DEFAULT_CONFIG from src.common_classification import (configure_model_cores, predictions (np.ndarray): Model predictions on test set.
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