Graph Models

GCNII

Introduced by Chen et al. in Simple and Deep Graph Convolutional Networks

GCNII is an extension of a Graph Convolution Networks with two new techniques, initial residual and identify mapping, to tackle the problem of oversmoothing -- where stacking more layers and adding non-linearity tends to degrade performance. At each layer, initial residual constructs a skip connection from the input layer, while identity mapping adds an identity matrix to the weight matrix.

Source: Simple and Deep Graph Convolutional Networks

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