Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/NDP

NDP

Reported on 8 benchmarks across 2 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Graphs4 results

Graph ClassificationonBench-hard
Accuracy· 2019-10-24
72.6
SOTA
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436
Graph ClassificationonMutagenicity
Accuracy· 2019-10-24
78.1
best: 83 (TREE-G)
SOTA
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436
Graph Classificationon5pt. Bench-Easy
Accuracy· 2019-10-24
97.9
SOTA
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436
Graph ClassificationonREDDIT-B
Accuracy· 2019-10-24
84.3
best: 93.15 (CRaWl)
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436

Methodology4 results

ClassificationonBench-hard
Accuracy· 2019-10-24
72.6
SOTA
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436
ClassificationonMutagenicity
Accuracy· 2019-10-24
78.1
best: 83 (TREE-G)
SOTA
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436
Classificationon5pt. Bench-Easy
Accuracy· 2019-10-24
97.9
SOTA
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436
ClassificationonREDDIT-B
Accuracy· 2019-10-24
84.3
best: 93.15 (CRaWl)
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling arXiv:1910.11436