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Open Graph Benchmark: Datasets for Machine Learning on Graphs
v1v2v3v4v5v6v7 (latest)

Open Graph Benchmark: Datasets for Machine Learning on Graphs

2 May 2020
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
ArXiv (abs)PDFHTML

Papers citing "Open Graph Benchmark: Datasets for Machine Learning on Graphs"

50 / 1,644 papers shown
Title
Uncovering Neural Scaling Laws in Molecular Representation Learning
Uncovering Neural Scaling Laws in Molecular Representation Learning
Dingshuo Chen
Yanqiao Zhu
Jieyu Zhang
Yuanqi Du
Zhixun Li
Qiang Liu
Shu Wu
Liang Wang
69
19
0
15 Sep 2023
A parameterised model for link prediction using node centrality and
  similarity measure based on graph embedding
A parameterised model for link prediction using node centrality and similarity measure based on graph embedding
Haohui Lu
Mohammed Shahadat Uddin
89
7
0
11 Sep 2023
UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge
  Graphs
UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge Graphs
Yide Qiu
Shaoxiang Ling
Tong Zhang
Bo Huang
Zhen Cui
98
0
0
11 Sep 2023
Circle Feature Graphormer: Can Circle Features Stimulate Graph
  Transformer?
Circle Feature Graphormer: Can Circle Features Stimulate Graph Transformer?
Jingsong Lv
Hongyang Chen
Yao Qi
Lei Yu
20
0
0
11 Sep 2023
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle
  Counting Power
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power
Junru Zhou
Jiarui Feng
Xiyuan Wang
Muhan Zhang
100
9
0
10 Sep 2023
Graph Neural Networks Use Graphs When They Shouldn't
Graph Neural Networks Use Graphs When They Shouldn't
Maya Bechler-Speicher
Ido Amos
Ran Gilad-Bachrach
Amir Globerson
GNNAI4CE
45
15
0
08 Sep 2023
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising
  and Cross-Modal Distillation
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation
Sungjun Cho
Dae-Woong Jeong
Sung Moon Ko
Jinwoo Kim
Sehui Han
Seunghoon Hong
Honglak Lee
Moontae Lee
AI4CEDiffM
63
1
0
08 Sep 2023
Pure Message Passing Can Estimate Common Neighbor for Link Prediction
Pure Message Passing Can Estimate Common Neighbor for Link Prediction
Kaiwen Dong
Zhichun Guo
Nitesh Chawla
109
8
0
02 Sep 2023
Rethinking the Power of Graph Canonization in Graph Representation
  Learning with Stability
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
Zehao Dong
Muhan Zhang
Philip R. O. Payne
Michael Province
C. Cruchaga
Tianyu Zhao
Fuhai Li
Yixin Chen
94
1
0
01 Sep 2023
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark
Jan Tönshoff
Martin Ritzert
Eran Rosenbluth
Martin Grohe
104
54
0
01 Sep 2023
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
Zehao Dong
Weidong Cao
Muhan Zhang
Dacheng Tao
Yixin Chen
Xuan Zhang
GNN
85
39
0
31 Aug 2023
Domain Generalization without Excess Empirical Risk
Domain Generalization without Excess Empirical Risk
Ozan Sener
V. Koltun
74
9
0
30 Aug 2023
An Experimental Comparison of Partitioning Strategies for Distributed
  Graph Neural Network Training
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training
Nikolai Merkel
Daniel Stoll
R. Mayer
Hans-Arno Jacobsen
GNN
82
2
0
29 Aug 2023
Structural Node Embeddings with Homomorphism Counts
Structural Node Embeddings with Homomorphism Counts
Hinrikus Wolf
Luca Oeljeklaus
Pascal Kuhner
Martin Grohe
81
3
0
29 Aug 2023
Class-Imbalanced Graph Learning without Class Rebalancing
Class-Imbalanced Graph Learning without Class Rebalancing
Zhining Liu
Ruizhong Qiu
Zhichen Zeng
Hyunsik Yoo
David Zhou
Zhe Xu
Yada Zhu
Kommy Weldemariam
Jingrui He
Hanghang Tong
AI4CE
84
12
0
27 Aug 2023
TpuGraphs: A Performance Prediction Dataset on Large Tensor
  Computational Graphs
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs
P. Phothilimthana
Sami Abu-El-Haija
Kaidi Cao
Bahare Fatemi
Mike Burrows
Charith Mendis
Bryan Perozzi
GNNAI4TS
127
20
0
25 Aug 2023
Staleness-Alleviated Distributed GNN Training via Online
  Dynamic-Embedding Prediction
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction
Guangji Bai
Ziyang Yu
Zheng Chai
Yue Cheng
Liang Zhao
GNN
94
3
0
25 Aug 2023
May the Force be with You: Unified Force-Centric Pre-Training for 3D
  Molecular Conformations
May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations
Rui Feng
Qi Zhu
Huan Tran
Binghong Chen
Aubrey Toland
R. Ramprasad
Chao Zhang
AI4CE
66
11
0
24 Aug 2023
A Survey of Graph Unlearning
A Survey of Graph Unlearning
Anwar Said
Hanyu Wang
Mudassir Shabbir
W. Abbas
X. Koutsoukos
MU
61
9
0
23 Aug 2023
Cached Operator Reordering: A Unified View for Fast GNN Training
Cached Operator Reordering: A Unified View for Fast GNN Training
Julia Bazinska
Andrei Ivanov
Tal Ben-Nun
Nikoli Dryden
Maciej Besta
Siyuan Shen
Torsten Hoefler
GNN
73
3
0
23 Aug 2023
Graph Neural Stochastic Differential Equations
Graph Neural Stochastic Differential Equations
Richard Bergna
Felix L. Opolka
Pietro Lio
Jose Miguel Hernandez-Lobato
57
3
0
23 Aug 2023
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution
  Networks
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks
Xiaoru Xie
Hongwu Peng
Amit Hasan
Shaoyi Huang
Jiahui Zhao
Haowen Fang
Wei Zhang
Tong Geng
O. Khan
Caiwen Ding
GNN
64
31
0
22 Aug 2023
Class Label-aware Graph Anomaly Detection
Class Label-aware Graph Anomaly Detection
Junghoon Kim
Yeonjun In
Kanghoon Yoon
Junmo Lee
Chanyoung Park
50
11
0
22 Aug 2023
Enhancing Graph Transformers with Hierarchical Distance Structural
  Encoding
Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
Yuan Luo
Hongkang Li
Lei Shi
Xiao-Ming Wu
93
8
0
22 Aug 2023
Geometric instability of graph neural networks on large graphs
Geometric instability of graph neural networks on large graphs
Emily L Morris
Haotian Shen
Weiling Du
Muhammad Hamza Sajjad
Borun Shi
GNN
103
0
0
19 Aug 2023
The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive
  field
The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field
Kun Wang
Guohao Li
Shilong Wang
Guibin Zhang
Kaidi Wang
Yang You
Xiaojiang Peng
Yuxuan Liang
Yang Wang
73
9
0
19 Aug 2023
Investigating the Interplay between Features and Structures in Graph
  Learning
Investigating the Interplay between Features and Structures in Graph Learning
Daniele Castellana
Federico Errica
101
4
0
18 Aug 2023
FRGNN: Mitigating the Impact of Distribution Shift on Graph Neural
  Networks via Test-Time Feature Reconstruction
FRGNN: Mitigating the Impact of Distribution Shift on Graph Neural Networks via Test-Time Feature Reconstruction
Ruitian Ding
Jielong Yang
Feng Ji
Xionghu Zhong
Linbo Xie
117
1
0
18 Aug 2023
Is Self-Supervised Pretraining Good for Extrapolation in Molecular
  Property Prediction?
Is Self-Supervised Pretraining Good for Extrapolation in Molecular Property Prediction?
Shun Takashige
Masatoshi Hanai
Toyotaro Suzumura
Limin Wang
Kenjiro Taura
64
1
0
16 Aug 2023
Language is All a Graph Needs
Language is All a Graph Needs
Ruosong Ye
Caiqi Zhang
Runhui Wang
Shuyuan Xu
Yongfeng Zhang
AI4CE
168
171
0
14 Aug 2023
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path
  Complexes
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes
Quang Truong
Peter Chin
GNN
94
9
0
13 Aug 2023
SAILOR: Structural Augmentation Based Tail Node Representation Learning
SAILOR: Structural Augmentation Based Tail Node Representation Learning
Jie Liao
Jintang Li
Liang Chen
Bing Wu
Yatao Bian
Zibin Zheng
65
4
0
13 Aug 2023
XFlow: Benchmarking Flow Behaviors over Graphs
XFlow: Benchmarking Flow Behaviors over Graphs
Zijian Zhang
Zonghan Zhang
Zhiqian Chen
45
0
0
07 Aug 2023
Communication-Free Distributed GNN Training with Vertex Cut
Communication-Free Distributed GNN Training with Vertex Cut
Kaidi Cao
Rui Deng
Shirley Wu
E-Wen Huang
Karthik Subbian
J. Leskovec
GNN
84
4
0
06 Aug 2023
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery
  Ticket
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Ticket
Yuwen Wang
Shunyu Liu
Kai Chen
Tongtian Zhu
Jilin Qiao
Mengjie Shi
Yuanyu Wan
Mingli Song
61
6
0
05 Aug 2023
Label Inference Attacks against Node-level Vertical Federated GNNs
Label Inference Attacks against Node-level Vertical Federated GNNs
Marco Arazzi
Mauro Conti
Stefanos Koffas
Marina Krček
Antonino Nocera
S. Picek
Jing Xu
FedMLAAML
57
1
0
04 Aug 2023
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and
  MLPs
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
Ling Yang
Ye Tian
Minkai Xu
Zhongyi Liu
Shenda Hong
Wei Qu
Wentao Zhang
Tengjiao Wang
Muhan Zhang
J. Leskovec
84
14
0
04 Aug 2023
SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning
SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning
Keyu Duan
Qian Liu
Tat-Seng Chua
Shuicheng Yan
Wei Tsang Ooi
Qizhe Xie
Junxian He
129
60
0
03 Aug 2023
HUGE: Huge Unsupervised Graph Embeddings with TPUs
HUGE: Huge Unsupervised Graph Embeddings with TPUs
Brandon Mayer
Anton Tsitsulin
Hendrik Fichtenberger
Jonathan J. Halcrow
Bryan Perozzi
GNN
60
1
0
26 Jul 2023
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph
  Contrastive Learning
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning
Yun Zhu
Haizhou Shi
Zhenshuo Zhang
Siliang Tang
132
9
0
24 Jul 2023
Addressing the Impact of Localized Training Data in Graph Neural
  Networks
Addressing the Impact of Localized Training Data in Graph Neural Networks
S. Akansha
78
3
0
24 Jul 2023
Extracting Molecular Properties from Natural Language with Multimodal
  Contrastive Learning
Extracting Molecular Properties from Natural Language with Multimodal Contrastive Learning
Romain Lacombe
Andrew Gaut
Jeff He
D. Lüdeke
Kateryna Pistunova
47
2
0
22 Jul 2023
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
Boshen Shi
Yongqing Wang
Fangda Guo
Jiangli Shao
Huawei Shen
Xueqi Cheng
OODAI4CE
50
6
0
21 Jul 2023
Anticipating Technical Expertise and Capability Evolution in Research
  Communities using Dynamic Graph Transformers
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph Transformers
Sameera Horawalavithana
Ellyn Ayton
A. Usenko
Robin Cosbey
Svitlana Volkova
AI4TS
62
0
0
18 Jul 2023
Sharpness-Aware Graph Collaborative Filtering
Sharpness-Aware Graph Collaborative Filtering
Huiyuan Chen
Chin-Chia Michael Yeh
Yujie Fan
Yan Zheng
Junpeng Wang
Vivian Lai
Mahashweta Das
Hao Yang
80
5
0
18 Jul 2023
Disentangling Node Attributes from Graph Topology for Improved
  Generalizability in Link Prediction
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction
Ayan Chatterjee
Robin Walters
G. Menichetti
Tina Eliassi-Rad
AI4CE
66
2
0
17 Jul 2023
Curriculum Learning for Graph Neural Networks: A Multiview
  Competence-based Approach
Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approach
Nidhi Vakil
Hadi Amiri
87
3
0
17 Jul 2023
Long-range Meta-path Search on Large-scale Heterogeneous Graphs
Long-range Meta-path Search on Large-scale Heterogeneous Graphs
Chao Li
Zijie Guo
Qiuting He
Hao Xu
Kun He
115
3
0
17 Jul 2023
Automated Polynomial Filter Learning for Graph Neural Networks
Automated Polynomial Filter Learning for Graph Neural Networks
Wendi Yu
Zhichao Hou
Xiaorui Liu
90
0
0
16 Jul 2023
Multi-Dimensional Ability Diagnosis for Machine Learning Algorithms
Multi-Dimensional Ability Diagnosis for Machine Learning Algorithms
Qi Liu
Zhengze Gong
Zhenya Huang
Chuanren Liu
Hengshu Zhu
Zhi Li
Enhong Chen
Hui Xiong
59
1
0
14 Jul 2023
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