AdaGPR

2000년 도입 · 논문 1편에서 사용

AdaGPR is an adaptive, layer-wise graph convolution model. AdaGPR applies adaptive generalized Pageranks at each layer of a GCNII model by learning to predict the coefficients of generalized Pageranks using sparse solvers.

출처: Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank

소개 논문: Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank