OpenCodePapers

node-classification-on-citeseer-60-20-20

Node Classification
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PaperCode1:1 AccuracyModelNameReleaseDate
GNNDLD: Graph Neural Network with Directional Label Distribution86.3±1.24GNNDLD2024-02-26
Beyond Low-frequency Information in Graph Convolutional Networks✓ Link82.37 ± 1.46FAGCN2021-01-04
Revisiting Heterophily For Graph Neural Networks✓ Link82.28 ± 1.12ACM-GCNII2022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link82.07 ± 1.04ACMII-Snowball-22022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link81.87 ± 1.38ACMII-GCN+2022-10-14
Simple and Deep Graph Convolutional Networks✓ Link81.83 ± 1.78GCNII*2020-07-04
Revisiting Heterophily For Graph Neural Networks✓ Link81.83 ± 1.65ACM-GCN++2022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link81.79 ± 0.95ACMII-GCN2022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link81.76 ± 1.25ACMII-GCN++2022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link81.69 ± 1.25ACM-GCNII*2022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link81.65 ± 1.48ACM-GCN+2022-10-14
Simple and Deep Graph Convolutional Networks✓ Link81.58 ± 1.3GCNII2020-07-04
Revisiting Heterophily For Graph Neural Networks✓ Link81.58 ± 1.23ACM-Snowball-22022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link81.56 ± 1.15ACMII-Snowball-32022-10-14
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks✓ Link81.53 ± 1.71Snowball-22019-06-05
Semi-Supervised Classification with Graph Convolutional Networks✓ Link81.39 ± 1.23GCN2016-09-09
Revisiting Heterophily For Graph Neural Networks✓ Link81.32 ± 0.97ACM-Snowball-32022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link80.96 ± 0.93ACM-SGC-12022-10-14
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks✓ Link80.93 ± 1.32Snowball-32019-06-05
Revisiting Heterophily For Graph Neural Networks✓ Link80.93 ± 1.16ACM-SGC-22022-10-14
Simplifying Graph Convolutional Networks✓ Link80.75 ± 1.15SGC-22019-02-19
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation✓ Link80.09 ± 0.79BernNet2021-06-21
Beyond Low-frequency Information in Graph Convolutional Networks✓ Link79.97 ± 0.69H2GCN2021-01-04
Simplifying Graph Convolutional Networks✓ Link79.66 ± 0.75SGC-12019-02-19
Inductive Representation Learning on Large Graphs✓ Link78.24 ± 0.30GraphSAGE2017-06-07
Geom-GCN: Geometric Graph Convolutional Networks✓ Link77.99Geom-GCN*2020-02-13
Revisiting Heterophily For Graph Neural Networks✓ Link76.25 ± 0.28MLP-22022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link74.49 ± 2.76 GAT+JK2022-10-14
Revisiting Heterophily For Graph Neural Networks✓ Link73.77 ± 1.85GCN+JK2022-10-14
Predict then Propagate: Graph Neural Networks meet Personalized PageRank✓ Link68.59 ± 0.30APPNP2018-10-14
Adaptive Universal Generalized PageRank Graph Neural Network✓ Link67.63 ± 0.38GPRGNN2020-06-14
Graph Attention Networks✓ Link67.20 ± 0.46GAT2017-10-30
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing✓ Link49.52 ± 13.35MixHop2019-04-30
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