HyperGraph Datasets
Collection
Collection of HyperGraph Datasets
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17 items
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Updated
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7
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1 | [1] | 3,547,497,600,000 |
2 | [2] | 1,594,425,600,000 |
6 | [5] | 3,499,459,200,000 |
7 | [5] | 3,499,459,200,000 |
8 | [6] | 3,193,689,600,000 |
9 | [7] | 3,247,257,600,000 |
10 | [7] | 3,247,257,600,000 |
11 | [7] | 3,247,257,600,000 |
12 | [8, 6] | 3,385,065,600,000 |
13 | [8, 6] | 3,281,212,800,000 |
14 | [8, 6] | 3,281,212,800,000 |
15 | [8, 6] | 3,281,212,800,000 |
16 | [8, 6] | 3,281,212,800,000 |
17 | [9] | 3,302,294,400,000 |
18 | [7] | 3,247,257,600,000 |
19 | [7] | 3,247,257,600,000 |
20 | [9] | 3,302,294,400,000 |
21 | [7] | 3,317,328,000,000 |
22 | [7] | 3,317,328,000,000 |
23 | [9] | 3,472,502,400,000 |
24 | [8] | 3,076,012,800,000 |
25 | [8] | 3,053,116,800,000 |
26 | [8] | 3,053,116,800,000 |
27 | [8] | 3,053,116,800,000 |
28 | [10] | 3,093,033,600,000 |
29 | [10] | 3,093,033,600,000 |
30 | [8] | 3,156,451,200,000 |
31 | [8] | 3,192,393,600,000 |
32 | [8] | 3,168,806,400,000 |
33 | [8] | 3,168,806,400,000 |
34 | [8] | 3,208,291,200,000 |
35 | [8] | 3,208,291,200,000 |
36 | [11] | 3,278,793,600,000 |
37 | [11] | 3,278,793,600,000 |
38 | [11] | 3,278,793,600,000 |
39 | [11] | 3,408,652,800,000 |
40 | [12] | 3,456,172,800,000 |
41 | [12] | 3,456,172,800,000 |
42 | [13] | 2,964,988,800,000 |
44 | [15] | 3,041,107,200,000 |
45 | [15] | 3,041,107,200,000 |
50 | [8] | 3,289,766,400,000 |
51 | [17] | 3,284,841,600,000 |
52 | [17] | 3,398,112,000,000 |
53 | [18] | 3,607,027,200,000 |
54 | [18] | 3,607,027,200,000 |
62 | [22] | 3,247,257,600,000 |
75 | [24] | 3,439,756,800,000 |
76 | [25] | 3,452,803,200,000 |
77 | [26] | 3,517,084,800,000 |
78 | [25] | 3,452,803,200,000 |
79 | [27] | 3,360,355,200,000 |
80 | [27] | 3,360,355,200,000 |
81 | [27] | 3,360,355,200,000 |
82 | [28] | 3,452,803,200,000 |
83 | [27] | 3,421,094,400,000 |
84 | [27] | 3,497,212,800,000 |
85 | [27] | 3,497,212,800,000 |
86 | [29] | 3,565,641,600,000 |
87 | [29] | 3,565,641,600,000 |
88 | [30] | 3,321,043,200,000 |
89 | [30] | 3,321,043,200,000 |
90 | [30] | 3,321,043,200,000 |
91 | [31] | 2,981,404,800,000 |
92 | [31] | 2,981,404,800,000 |
93 | [31] | 2,981,404,800,000 |
94 | [31] | 2,981,404,800,000 |
95 | [31] | 3,050,956,800,000 |
96 | [32] | 3,439,756,800,000 |
97 | [32] | 3,520,886,400,000 |
98 | [33] | 3,479,068,800,000 |
99 | [33] | 3,479,068,800,000 |
101 | [35] | 3,510,000,000,000 |
102 | [35] | 3,510,000,000,000 |
103 | [33] | 3,479,068,800,000 |
104 | [33] | 3,479,068,800,000 |
105 | [32] | 3,520,886,400,000 |
106 | [32] | 3,520,886,400,000 |
107 | [36] | 3,265,401,600,000 |
108 | [36] | 3,265,401,600,000 |
109 | [36] | 3,265,401,600,000 |
115 | [39] | 3,452,803,200,000 |
116 | [39] | 3,452,803,200,000 |
117 | [39] | 3,452,803,200,000 |
118 | [28] | 3,452,803,200,000 |
119 | [28] | 3,452,803,200,000 |
120 | [28] | 3,452,803,200,000 |
121 | [40] | 3,194,812,800,000 |
122 | [40] | 3,460,406,400,000 |
123 | [41] | 2,379,888,000,000 |
124 | [41] | 2,379,888,000,000 |
126 | [41] | 2,379,888,000,000 |
127 | [43] | 3,235,680,000,000 |
128 | [43] | 3,515,875,200,000 |
129 | [44] | 3,312,230,400,000 |
130 | [44] | 3,027,196,800,000 |
131 | [45] | 3,501,532,800,000 |
132 | [46] | 3,008,448,000,000 |
133 | [46] | 3,075,667,200,000 |
134 | [46] | 3,116,188,800,000 |
Source Paper: https://arxiv.org/abs/1802.06916
from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset
dataset = CornellTemporalHyperGraphDataset(root = "./", name="NDC-substances-25", split="train")
@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}
}