Check leaderboards for
The bold method name indicates that the implementation is official (by the author of the original paper).
Package denotes the required package version for each dataset to be eligible for the leaderboard.
The ROC-AUC score on the test and validation sets. The higher, the better.
Package: >=1.1.1
| Rank |
Method |
Ext. data |
Test ROC-AUC |
Validation ROC-AUC |
Contact |
References |
#Params |
Hardware |
Date |
| 1 |
HyperFusion |
No |
0.8475 ± 0.0003 |
0.8275 ± 0.0008 |
Xinwei Zhang(Tsinghua University) |
Paper, Code |
5,908,027 |
RTX 3080 |
Feb 24, 2024 |
| 2 |
PAS+FPs |
No |
0.8420 ± 0.0015 |
0.8238 ± 0.0028 |
Xu Wang(4Paradigm) |
Paper, Code |
26,706,953 |
RTX3090 |
Feb 22, 2022 |
| 3 |
HIG |
No |
0.8403 ± 0.0021 |
0.8176 ± 0.0034 |
Yan Wang (Tencent Youtu Lab) |
Paper, Code |
1,019,408 |
Tesla V100 (32GB) |
Dec 28, 2021 |
| 4 |
DeepAUC |
No |
0.8352 ± 0.0054 |
0.8238 ± 0.0061 |
Zhuoning Yuan (UIowa) |
Paper, Code |
3,444,509 |
Tesla V100 (32GB) |
Oct 10, 2021 |
| 5 |
FingerPrint+GMAN |
No |
0.8244 ± 0.0033 |
0.8329 ± 0.0039 |
Jiaxin Gu |
Paper, Code |
1,444,110 |
Tesla V100 (32GB) |
Jul 8, 2021 |
| 6 |
Neural FingerPrints |
No |
0.8232 ± 0.0047 |
0.8331 ± 0.0054 |
Shanzhuo Zhang (PaddleHelix & PGL) |
Paper, Code |
2,425,102 |
Tesla V100 (32GB) |
Mar 15, 2021 |
| 7 |
Graphormer + FPs |
No |
0.8225 ± 0.0001 |
0.8396 ± 0.0001 |
Huixuan Chi (AML@ByteDance) |
Paper, Code |
47,085,378 |
Tesla V100 (32GB) |
Aug 5, 2021 |
| 8 |
Molecular FP + Random Forest |
No |
0.8208 ± 0.0037 |
0.8036 ± 0.0059 |
Luca Hagemeyer |
Paper, Code |
5,782 |
CPU |
Mar 18, 2022 |
| 9 |
CIN |
No |
0.8094 ± 0.0057 |
0.8277 ± 0.0099 |
Fabrizio Frasca (Twitter) |
Paper, Code |
239,745 |
Tesla V100 (16GB) |
Aug 31, 2021 |
| 10 |
GSAT |
No |
0.8067 ± 0.0950 |
0.8347 ± 0.0031 |
Siqi Miao (Purdue) |
Paper, Code |
249,602 |
Quadro RTX 6000 |
May 15, 2022 |
| 11 |
MorganFP+Rand. Forest |
No |
0.8060 ± 0.0010 |
0.8420 ± 0.0030 |
Cyrus Maher |
Paper, Code |
230,000 |
CPU |
Sep 21, 2020 |
| 12 |
CIN-small |
No |
0.8055 ± 0.0104 |
0.8310 ± 0.0102 |
Fabrizio Frasca (Twitter) |
Paper, Code |
138,337 |
Tesla V100 (16GB) |
Aug 31, 2021 |
| 13 |
Graphormer (pre-trained on PCQM4M) |
Yes |
0.8051 ± 0.0053 |
0.8310 ± 0.0089 |
Shuxin Zheng (Microsoft Research) |
Paper, Code |
47,183,040 |
NVIDIA Tesla V100 (16GB GPU) |
Aug 2, 2021 |
| 14 |
directional GSN |
No |
0.8039 ± 0.0090 |
0.8473 ± 0.0096 |
Giorgos Bouritsas (Imperial College) |
Paper, Code |
114,211 |
Tesla V100 (32GB) |
Jul 28, 2021 |
| 14 |
P-WL |
No |
0.8039 ± 0.0040 |
0.8279 ± 0.0059 |
Daniel Marcos Mendoza |
Paper, Code |
4,600,000 |
CPU |
Mar 29, 2021 |
| 15 |
DGN |
No |
0.7970 ± 0.0097 |
0.8470 ± 0.0047 |
Saro Passaro |
Paper, Code |
114,065 |
NVIDIA Tesla T4 (15GB GPU) |
Nov 20, 2020 |
| 16 |
DeeperGCN+FLAG |
No |
0.7942 ± 0.0120 |
0.8425 ± 0.0061 |
Kezhi Kong |
Paper, Code |
531,976 |
NVIDIA Tesla V100 (32GB GPU) |
Oct 20, 2020 |
| 17 |
PHC-GNN |
No |
0.7934 ± 0.0116 |
0.8217 ± 0.0089 |
Tuan Le |
Paper, Code |
110,909 |
Tesla V100 (32GB) |
Apr 14, 2021 |
| 18 |
PNA |
No |
0.7905 ± 0.0132 |
0.8519 ± 0.0099 |
Gabriele Corso |
Paper, Code |
326,081 |
NVIDIA Tesla T4 (15GB GPU) |
Nov 25, 2020 |
| 19 |
GCN+GraphNorm |
No |
0.7883 ± 0.0100 |
0.7904 ± 0.0115 |
Shengjie Luo |
Paper, Code |
526,201 |
NVIDIA Tesla P100 (16GB GPU) |
Sep 16, 2020 |
| 20 |
HIMP |
No |
0.7880 ± 0.0082 |
Please tell us |
Matthias Fey |
Paper, Code |
153,029 |
GeForce RTX 2080 (11GB GPU) |
Jun 22, 2020 |
| 21 |
DeeperGCN |
No |
0.7858 ± 0.0117 |
0.8427 ± 0.0063 |
Guohao Li - DeepGCNs.org |
Paper, Code |
531,976 |
NVIDIA Tesla V100 (32GB GPU) |
Jun 16, 2020 |
| 22 |
EGC-M (No Edge Features) |
No |
0.7818 ± 0.0153 |
0.8396 ± 0.0097 |
Shyam Tailor |
Paper, Code |
317,265 |
GTX1080Ti/RTX2080Ti |
Apr 6, 2021 |
| 23 |
GSN |
No |
0.7799 ± 0.0100 |
0.8658 ± 0.0084 |
Giorgos Bouritsas |
Paper, Code |
3,338,701 |
NVIDIA Tesla V100-SXM2 (16GB) |
Jan 5, 2021 |
| 24 |
GIN |
No |
0.7778 ± 0.0130 |
0.8325 ± 0.0151 |
Yunxin Sang(SJTU) |
Paper, Code |
7 |
Tesla T4 |
Apr 30, 2022 |
| 25 |
WEGL |
No |
0.7757 ± 0.0111 |
0.8101 ± 0.0097 |
Navid Naderializadeh |
Paper, Code |
361,064 |
NVIDIA Tesla P100 (16GB GPU) |
Jun 26, 2020 |
| 26 |
GIN+virtual node+FLAG |
No |
0.7748 ± 0.0096 |
0.8438 ± 0.0128 |
Kezhi Kong |
Paper, Code |
3,336,306 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 20, 2020 |
| 27 |
EGC-S (No Edge Features) |
No |
0.7721 ± 0.0110 |
0.8366 ± 0.0074 |
Shyam Tailor |
Paper, Code |
317,013 |
GTX1080Ti/RTX2080T |
Apr 6, 2021 |
| 28 |
GIN+virtual node |
No |
0.7707 ± 0.0149 |
0.8479 ± 0.0068 |
Weihua Hu – OGB team |
Paper, Code |
3,336,306 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 29 |
GCN+FLAG |
No |
0.7683 ± 0.0102 |
0.8176 ± 0.0087 |
Kezhi Kong |
Paper, Code |
527,701 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 20, 2020 |
| 30 |
GIN+FLAG |
No |
0.7654 ± 0.0114 |
0.8225 ± 0.0155 |
Kezhi Kong |
Paper, Code |
1,885,206 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 20, 2020 |
| 31 |
GCN |
No |
0.7606 ± 0.0097 |
0.8204 ± 0.0141 |
Weihua Hu – OGB team |
Paper, Code |
527,701 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 32 |
GCN+virtual node |
No |
0.7599 ± 0.0119 |
0.8384 ± 0.0091 |
Weihua Hu – OGB team |
Paper, Code |
1,978,801 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 33 |
GIN |
No |
0.7558 ± 0.0140 |
0.8232 ± 0.0090 |
Weihua Hu – OGB team |
Paper, Code |
1,885,206 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 34 |
GCN (in Julia) |
No |
0.7549 ± 0.0163 |
0.8042 ± 0.0107 |
Irhum Shafkat (Minerva) |
Paper, Code |
527,701 |
Tesla T4 (16GB) |
Jun 28, 2021 |
The Average Precision (AP) score on the test and validation sets. The higher, the better.
Note: The evaluation metric has been changed from PRC-AUC (Aug 11, 2020).
Package: >=1.2.2
| Rank |
Method |
Ext. data |
Test AP |
Validation AP |
Contact |
References |
#Params |
Hardware |
Date |
| 1 |
HyperFusion |
No |
0.3204 ± 0.0001 |
0.3353 ± 0.0002 |
Xinwei Zhang (Tsinghua University) |
Paper, Code |
10,887,085 |
RTX 3080 |
Feb 24, 2024 |
| 2 |
HIG(pre-trained on PCQM4M) |
Yes |
0.3167 ± 0.0034 |
0.3252 ± 0.0043 |
Yan Wang (Tencent Youtu Lab) |
Paper, Code |
119,529,665 |
Tesla V100 (32GB) |
Dec 28, 2021 |
| 3 |
Graphormer (pre-trained on PCQM4M) |
Yes |
0.3140 ± 0.0032 |
0.3227 ± 0.0024 |
Shuxin Zheng (Microsoft) |
Paper, Code |
119,529,664 |
NVIDIA Tesla V100 (16GB GPU) |
Aug 2, 2021 |
| 4 |
PDF |
No |
0.3031 ± 0.0026 |
0.3115 ± 0.0020 |
Mingqi Yang |
Paper, Code |
3,842,048 |
Tesla A100 (40GB) |
May 12, 2023 |
| 5 |
PAS |
No |
0.3012 ± 0.0039 |
0.3151 ± 0.0047 |
Xu Wang(4Paradigm) |
Paper, Code |
5,560,960 |
RTX3090 |
Apr 1, 2022 |
| 6 |
Nested GIN+virtual node (ensemble) |
No |
0.3007 ± 0.0037 |
0.3059 ± 0.0056 |
Muhan Zhang |
Paper, Code |
44,187,480 |
NVIDIA Tesla V100 (32GB GPU) |
Nov 21, 2021 |
| 7 |
GINE+bot |
No |
0.2994 ± 0.0019 |
0.3094 ± 0.0023 |
Hao Zhang |
Paper, Code |
5,511,680 |
Tesla V100(32GB GPU) |
Jul 21, 2021 |
| 8 |
CRaWl |
No |
0.2986 ± 0.0025 |
0.3075 ± 0.0020 |
Jan Tönshoff (RWTH Aachen University) |
Paper, Code |
6,115,728 |
Nvidia Tesla V100 (16GB) |
Mar 27, 2022 |
| 9 |
GINE+ w/ APPNP |
No |
0.2979 ± 0.0030 |
0.3126 ± 0.0023 |
Weibin Li (PaddleHelix & PGL) |
Paper, Code |
6,147,029 |
Tesla V100 (32GB) |
Mar 15, 2021 |
| 10 |
PHC-GNN |
No |
0.2947 ± 0.0026 |
0.3068 ± 0.0025 |
Tuan Le |
Paper, Code |
1,690,328 |
Tesla V100 (32GB) |
Apr 14, 2021 |
| 11 |
GIN-AK |
No |
0.2930 ± 0.0044 |
0.3047 ± 0.0007 |
Lingxiao Zhao |
Paper, Code |
3,081,029 |
RTX 3090 |
Oct 11, 2021 |
| 12 |
GINE+ w/ virtual nodes |
No |
0.2917 ± 0.0015 |
0.3065 ± 0.0030 |
Rémy Brossard |
Paper, Code |
6,147,029 |
GeForce GTX 1080 Ti |
Dec 1, 2020 |
| 13 |
DGN |
No |
0.2885 ± 0.0030 |
0.2970 ± 0.0021 |
Dominique Beaini |
Paper, Code |
6,732,696 |
NVIDIA T4 GPU (16 GB) |
Mar 4, 2021 |
| 14 |
RandomGIN-vn+FLAG |
No |
0.2881 ± 0.0028 |
0.3035 ± 0.0047 |
Giulia Fracastoro (Polito) |
Paper, Code |
5,572,026 |
Titan Xp (12GB GPU) |
Jul 29, 2021 |
| 15 |
DeeperGCN+virtual node+FLAG |
No |
0.2842 ± 0.0043 |
0.2952 ± 0.0029 |
Kezhi Kong |
Paper, Code |
5,550,208 |
NVIDIA Tesla V100 (32GB GPU) |
Oct 21, 2020 |
| 16 |
PNA |
No |
0.2838 ± 0.0035 |
0.2926 ± 0.0026 |
Dominique Beaini |
Paper, Code |
6,550,839 |
NVIDIA T4 GPU (16 GB) |
Mar 4, 2021 |
| 17 |
GIN+virtual node+FLAG |
No |
0.2834 ± 0.0038 |
0.2912 ± 0.0026 |
Kezhi Kong |
Paper, Code |
3,374,533 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 18 |
DeeperGCN+virtual node |
No |
0.2781 ± 0.0038 |
0.2920 ± 0.0025 |
Guohao Li - DeepGCNs.org |
Paper, Code |
5,550,208 |
NVIDIA Tesla V100 (32GB GPU) |
Aug 11, 2020 |
| 19 |
GIN+virtual node |
No |
0.2703 ± 0.0023 |
0.2798 ± 0.0025 |
Weihua Hu – OGB team |
Paper, Code |
3,374,533 |
GeForce RTX 2080 (11GB GPU) |
Aug 11, 2020 |
| 20 |
GCN+virtual node+FLAG |
No |
0.2483 ± 0.0037 |
0.2556 ± 0.0040 |
Kezhi Kong |
Paper, Code |
2,017,028 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 21 |
GCN+virtual node |
No |
0.2424 ± 0.0034 |
0.2495 ± 0.0042 |
Weihua Hu – OGB team |
Paper, Code |
2,017,028 |
GeForce RTX 2080 (11GB GPU) |
Aug 11, 2020 |
| 22 |
GIN+FLAG |
No |
0.2395 ± 0.0040 |
0.2451 ± 0.0042 |
Kezhi Kong |
Paper, Code |
1,923,433 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 23 |
ChebNet |
No |
0.2306 ± 0.0016 |
0.2372 ± 0.0018 |
Axel Nilsson |
Paper, Code |
1,475,003 |
GeForce RTX 2070 8GB |
Dec 28, 2020 |
| 24 |
GIN |
No |
0.2266 ± 0.0028 |
0.2305 ± 0.0027 |
Weihua Hu – OGB team |
Paper, Code |
1,923,433 |
GeForce RTX 2080 (11GB GPU) |
Aug 11, 2020 |
| 25 |
GCN+FLAG |
No |
0.2116 ± 0.0017 |
0.2150 ± 0.0022 |
Kezhi Kong |
Paper, Code |
565,928 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 26 |
MorganFP+Rand. Forest |
No |
0.2054 ± 0.0004 |
0.2226 ± 0.0002 |
Cyrus Maher |
Paper, Code |
29,440,000 |
CPU |
Sep 21, 2020 |
| 27 |
GCN |
No |
0.2020 ± 0.0024 |
0.2059 ± 0.0033 |
Weihua Hu – OGB team |
Paper, Code |
565,928 |
GeForce RTX 2080 (11GB GPU) |
Aug 11, 2020 |
The multi-class classification accuracy on the test and validation sets. The higher, the better.
Package: >=1.1.1
| Rank |
Method |
Ext. data |
Test Accuracy |
Validation Accuracy |
Contact |
References |
#Params |
Hardware |
Date |
| 1 |
PAS+F2GNN |
No |
0.8201 ± 0.0019 |
0.7720 ± 0.0023 |
Xu Wang(4Paradigm && EE Tsinghua) |
Paper, Code |
16,346,166 |
RTX 3090 |
Apr 28, 2022 |
| 2 |
ExpC*+bag of tricks |
No |
0.8140 ± 0.0028 |
0.7811 ± 0.0012 |
Hao Zhang |
Paper, Code |
3,758,642 |
Tesla V100(32GB GPU) |
Jun 21, 2021 |
| 3 |
ExpC |
No |
0.7976 ± 0.0072 |
0.7518 ± 0.0080 |
Mingqi Yang |
Paper, Code |
1,369,397 |
NVIDIA Tesla V100 (32GB GPU) |
Dec 14, 2020 |
| 4 |
PAS |
No |
0.7828 ± 0.0024 |
0.7523 ± 0.0028 |
Xu Wang(4Paradigm) |
Paper, Code |
3,717,160 |
RTX 3090 |
Mar 29, 2022 |
| 5 |
DeeperGCN+FLAG |
No |
0.7752 ± 0.0069 |
0.7484 ± 0.0052 |
Kezhi Kong |
Paper, Code |
2,336,421 |
NVIDIA Tesla V100 (32GB GPU) |
Oct 21, 2020 |
| 6 |
DeeperGCN |
No |
0.7712 ± 0.0071 |
0.7313 ± 0.0078 |
Guohao Li - DeepGCNs.org |
Paper, Code |
2,336,421 |
NVIDIA Tesla V100 (32GB GPU) |
Jun 16, 2020 |
| 7 |
GC-T+MCL(6.0) |
No |
0.7432 ± 0.0033 |
0.6989 ± 0.0037 |
Shuai Wang(SCMZU) |
Paper, Code |
4,006,704 |
RTX 3090 |
Jul 31, 2022 |
| 8 |
GIN+virtual node+FLAG |
No |
0.7245 ± 0.0114 |
0.6789 ± 0.0079 |
Kezhi Kong |
Paper, Code |
3,288,042 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 9 |
GIN+virtual node |
No |
0.7037 ± 0.0107 |
0.6678 ± 0.0105 |
Weihua Hu – OGB team |
Paper, Code |
3,288,042 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 10 |
GCN+virtual node+FLAG |
No |
0.6944 ± 0.0052 |
0.6638 ± 0.0055 |
Kezhi Kong |
Paper, Code |
1,930,537 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 11 |
GIN+FLAG |
No |
0.6905 ± 0.0092 |
0.6465 ± 0.0070 |
Kezhi Kong |
Paper, Code |
1,836,942 |
GeForce RTX 2080 Ti (11GB GPU) |
Oct 21, 2020 |
| 12 |
GIN |
No |
0.6892 ± 0.0100 |
0.6562 ± 0.0107 |
Weihua Hu – OGB team |
Paper, Code |
1,836,942 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 13 |
GCN+virtual node |
No |
0.6857 ± 0.0061 |
0.6511 ± 0.0048 |
Weihua Hu – OGB team |
Paper, Code |
1,930,537 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
| 14 |
GCN |
No |
0.6839 ± 0.0084 |
0.6497 ± 0.0034 |
Weihua Hu – OGB team |
Paper, Code |
479,437 |
GeForce RTX 2080 (11GB GPU) |
May 1, 2020 |
The F1 score on the test and validation sets. The higher, the better.
Package: >=1.2.5
Deprecated ogbg-code leaderboard can be found here.
| Rank |
Method |
Ext. data |
Test F1 score |
Validation F1 score |
Contact |
References |
#Params |
Hardware |
Date |
| 1 |
SAT++ with Magnetic Laplacian |
No |
0.2222 ± 0.0032 |
0.2044 ± 0.0020 |
Simon Geisler (TU Munich) |
Paper, Code |
14,378,069 |
4 Google Cloud TPUv4 |
Jan 13, 2023 |
| 2 |
DAGformer |
No |
0.2018 ± 0.0021 |
0.1846 ± 0.0010 |
Yuankai Luo (BUAA) |
Paper, Code |
14,952,882 |
GeForce RTX 3090 |
Oct 25, 2022 |
| 3 |
SAT |
No |
0.1937 ± 0.0028 |
0.1773 ± 0.0023 |
Dexiong Chen (ETH Zürich) |
Paper, Code |
15,734,000 |
1 Titan RTX |
Jun 20, 2022 |
| 4 |
GraphTrans (GCN-Virtual) |
No |
0.1830 ± 0.0024 |
0.1661 ± 0.0012 |
Zhanghao Wu (UC Berkeley) |
Paper, Code |
9,053,246 |
Tesla V100 (32GB GPU) |
Jan 15, 2022 |
| 5 |
GMAN+bag of tricks |
No |
0.1770 ± 0.0012 |
0.1631 ± 0.0090 |
Hao Zhang |
Paper, Code |
63,684,290 |
Tesla V100 (32GB GPU) |
Jun 21, 2021 |
| 6 |
DAGNN |
No |
0.1751 ± 0.0049 |
0.1607 ± 0.0040 |
Veronika Thost |
Paper, Code |
35,246,814 |
2 GPUs, Tesla V100 PCIe 16GB |
Apr 8, 2021 |
| 6 |
GraphTrans (GCN) |
No |
0.1751 ± 0.0015 |
0.1599 ± 0.0009 |
Zhanghao Wu (UC Berkeley) |
Paper, Code |
7,563,746 |
Tesla V100 (32GB GPU) |
Jan 15, 2022 |
| 7 |
GCN+virtual node |
No |
0.1595 ± 0.0018 |
0.1461 ± 0.0013 |
Weihua Hu – OGB team |
Paper, Code |
12,484,310 |
GeForce RTX 2080 (11GB GPU) |
Feb 24, 2021 |
| 7 |
EGC-M (No Edge Features) |
No |
0.1595 ± 0.0019 |
0.1464 ± 0.0021 |
Shyam Tailor |
Paper, Code |
10,986,002 |
GTX1080Ti/RTX2080Ti |
Apr 6, 2021 |
| 8 |
GIN+virtual node |
No |
0.1581 ± 0.0026 |
0.1439 ± 0.0020 |
Weihua Hu – OGB team |
Paper, Code |
13,841,815 |
GeForce RTX 2080 (11GB GPU) |
Feb 24, 2021 |
| 9 |
PNA (No Edge Features) |
No |
0.1570 ± 0.0032 |
0.1453 ± 0.0025 |
Shyam Tailor |
Paper, Code |
10,992,050 |
V100 |
Apr 6, 2021 |
| 10 |
GAT |
No |
0.1569 ± 0.0010 |
0.1442 ± 0.0017 |
Yuankai Luo (BUAA) |
Paper, Code |
11,030,210 |
GeForce RTX 3090 |
Jan 15, 2023 |
| 11 |
MPNN-Max (No Edge Features) |
No |
0.1552 ± 0.0022 |
0.1441 ± 0.0016 |
Shyam Tailor |
Paper, Code |
10,971,506 |
GTX1080Ti/RTX2080Ti |
Apr 6, 2021 |
| 12 |
EGC-S (No Edge Features) |
No |
0.1528 ± 0.0025 |
0.1427 ± 0.0020 |
Shyam Tailor |
Paper, Code |
11,156,530 |
GTX1080Ti/RTX2080Ti |
Apr 6, 2021 |
| 13 |
GCN |
No |
0.1507 ± 0.0018 |
0.1399 ± 0.0017 |
Weihua Hu – OGB team |
Paper, Code |
11,033,210 |
GeForce RTX 2080 (11GB GPU) |
Feb 24, 2021 |
| 14 |
GIN |
No |
0.1495 ± 0.0023 |
0.1376 ± 0.0016 |
Weihua Hu – OGB team |
Paper, Code |
12,390,715 |
GeForce RTX 2080 (11GB GPU) |
Feb 24, 2021 |
| 15 |
DiffPool w/ graphSAGE |
No |
0.1401 ± 0.0012 |
0.1405 ± 0.0012 |
“Nathanael” Yu Ren (Stanford) |
Paper, Code |
10,095,826 |
V100 |
Dec 17, 2023 |