class dgl.nn.tensorflow.conv.APPNPConv(*args, **kwargs)[source]

Bases: tensorflow.python.keras.engine.base_layer.Layer

Approximate Personalized Propagation of Neural Predictions layer from Predict then Propagate: Graph Neural Networks meet Personalized PageRank

\[ \begin{align}\begin{aligned}H^{0} & = X\\H^{t+1} & = (1-\alpha)\left(\hat{D}^{-1/2} \hat{A} \hat{D}^{-1/2} H^{t}\right) + \alpha H^{0}\end{aligned}\end{align} \]
  • k (int) – Number of iterations \(K\).

  • alpha (float) – The teleport probability \(\alpha\).

  • edge_drop (float, optional) – Dropout rate on edges that controls the messages received by each node. Default: 0.