Gradformer: A Machine Learning Method that Integrates Graph Transformers (GTs) with the Intrinsic Inductive Bias by Applying an Exponential Decay Mask to the Attention Matrix

Graph Transformers (GTs) have successfully achieved state-of-the-art performance on various platforms. GTs can capture long-range information from nodes that are at large distances, unlike the local message-passing in graph neural networks (GNNs). In addition, the self-attention mechanism in GTs permits each node to look at other nodes in a graph directly, helping collect information from […]

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