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Datasets:
SauravMaheshkar
/
congress-bills-25

Tasks:
Graph Machine Learning
Modalities:
Tabular
Text
Size:
100K - 1M
ArXiv:
Tags:
chemistry
License:
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Source Paper: https://arxiv.org/abs/1802.06916

Usage 

from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset

dataset = CornellTemporalHyperGraphDataset(root = "./", name="congress-bills-25", split="train")

Citation 

@article{Benson-2018-simplicial,
 author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon},
 title = {Simplicial closure and higher-order link prediction},
 year = {2018},
 doi = {10.1073/pnas.1800683115},
 publisher = {National Academy of Sciences},
 issn = {0027-8424},
 journal = {Proceedings of the National Academy of Sciences}
}
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