Node Classification On Penn94

المقاييس

Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

جدول المقارنة

اسم النموذج	Accuracy
joint-adaptive-feature-smoothing-and-topology	81.38 ± 0.16
new-benchmarks-for-learning-on-non	80.69 ± 0.36
simple-and-deep-graph-convolutional-networks-1	82.92 ± 0.59
new-benchmarks-for-learning-on-non	74.13 ± 0.46
mixture-of-experts-meets-decoupled-message	85.11±0.39
diffusion-jump-gnns-homophiliation-via	84.84±0.34
combining-label-propagation-and-simple-models-1	78.40 ± 3.12
new-benchmarks-for-learning-on-non	81.63 ± 0.54
combining-label-propagation-and-simple-models-1	74.28 ± 1.19
new-benchmarks-for-learning-on-non	63.21 ± 0.39
simplifying-graph-convolutional-networks	76.09 ± 0.45
finding-global-homophily-in-graph-neural	85.57 ± 0.35
simplifying-graph-convolutional-networks	66.79 ± 0.27
new-benchmarks-for-learning-on-non	80.79 ± 0.49
mixhop-higher-order-graph-convolution	83.47 ± 0.71
generalizing-graph-neural-networks-beyond	81.31 ± 0.60
new-benchmarks-for-learning-on-non	73.61 ± 0.40
clarify-confused-nodes-through-separated	84.74 ± 0.28
revisiting-heterophily-for-graph-neural	85.05 ± 0.19
revisiting-heterophily-for-graph-neural	84.95 ± 0.43
revisiting-heterophily-for-graph-neural	85.95 ± 0.26
mixture-of-experts-meets-decoupled-message	81.98±0.47
clarify-confused-nodes-through-separated	81.77 ± 0.71
semi-supervised-classification-with-graph	82.47 ± 0.27
predict-then-propagate-graph-neural-networks	74.33 ± 0.38
feature-selection-key-to-enhance-node	86.09±0.56
large-scale-learning-on-non-homophilous	84.71 ± 0.52
breaking-the-limit-of-graph-neural-networks	74.32 ± 0.53
revisiting-heterophily-for-graph-neural	86.08 ± 0.43
graph-attention-networks	81.53 ± 0.55
mixture-of-experts-meets-decoupled-message	84.05±0.37
finding-global-homophily-in-graph-neural	85.74±0.42