Node Classification On Ppi

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

جدول المقارنة

اسم النموذج	F1
sgas-sequential-greedy-architecture-search	99.46
a-proposal-of-multi-layer-perceptron-with	99.71
representation-learning-on-graphs-with	97.6
large-scale-learnable-graph-convolutional	77.2
simple-and-deep-graph-convolutional-networks-1	99.56
deepgcns-making-gcns-go-as-deep-as-cnns	99.43
the-split-matters-flat-minima-methods-for	99.38 ± 0.01%
cluster-gcn-an-efficient-algorithm-for	92.9
bridging-the-gap-between-spectral-and-spatial	99.09 ± 0.03
graph-representation-learning-beyond-node-and	-
graph-star-net-for-generalized-multi-task-1	99.4
deepgcns-making-gcns-go-as-deep-as-cnns	99.41
graphnas-graph-neural-architecture-search	98.6 ± 0.1
deep-graph-contrastive-representation	66.2
gaan-gated-attention-networks-for-learning-on	98.7
graphsaint-graph-sampling-based-inductive	99.50
graph-attention-networks	97.3
sign-scalable-inception-graph-neural-networks	96.50
the-split-matters-flat-minima-methods-for	99.34 ± 0.02%
cluster-gcn-an-efficient-algorithm-for	99.36
vq-gnn-a-universal-framework-to-scale-up	97.37
inductive-representation-learning-on-large	61.2