Open Graph Benchmark: Datasets for Machine Learning on Graphs

2 May 2020

Yuxiao Dong

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

50 / 1,609 papers shown

Title
SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolutional Networks Haimin Zhang Min Xu Guoqiang Zhang Kenta Niwa 16 8 0 20 Feb 2021
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective Stephen Bonner Ian P Barrett Cheng Ye Rowan Swiers O. Engkvist A. Bender Charles Tapley Hoyt William L. Hamilton 32 94 0 19 Feb 2021
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development Kexin Huang Tianfan Fu Wenhao Gao Yue Zhao Yusuf Roohani J. Leskovec Connor W. Coley Cao Xiao Jimeng Sun Marinka Zitnik OOD LM&MA 38 264 0 18 Feb 2021
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing Jan Toenshoff Martin Ritzert Hinrikus Wolf Martin Grohe GNN 84 29 0 17 Feb 2021
Fast Graph Learning with Unique Optimal Solutions Sami Abu-El-Haija V. Crespi Greg Ver Steeg Aram Galstyan 13 0 0 17 Feb 2021
How Framelets Enhance Graph Neural Networks Xuebin Zheng Bingxin Zhou Junbin Gao Yu Guang Wang Pietro Lio Ming Li Guido Montúfar 59 69 0 13 Feb 2021
Large-Scale Representation Learning on Graphs via Bootstrapping S. Thakoor Corentin Tallec M. G. Azar Mehdi Azabou Eva L. Dyer Rémi Munos Petar Velivcković Michal Valko SSL 29 217 0 12 Feb 2021
Memory-Associated Differential Learning Yi Luo Aiguo Chen Bei Hui Ke Yan 44 3 0 10 Feb 2021
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks Bahare Fatemi Layla El Asri Seyed Mehran Kazemi GNN SSL 22 160 0 09 Feb 2021
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning Elan Markowitz Keshav Balasubramanian Mehrnoosh Mirtaheri Sami Abu-El-Haija Bryan Perozzi Greg Ver Steeg Aram Galstyan 22 22 0 08 Feb 2021
Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations Dawei Leng Jinjiang Guo Lurong Pan Jie Li Xinyu Wang GNN 11 9 0 08 Feb 2021
Learning Conjoint Attentions for Graph Neural Nets Tiantian He Yew-Soon Ong Lu Bai GNN 22 52 0 05 Feb 2021
The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance Ajitesh Srivastava T. Xu Viktor Prasanna 12 1 0 04 Feb 2021
Calibrating and Improving Graph Contrastive Learning Kaili Ma Haochen Yang Han Yang Yongqiang Chen James Cheng 47 6 0 27 Jan 2021
Identity-aware Graph Neural Networks Jiaxuan You Jonathan M. Gomes-Selman Rex Ying J. Leskovec 19 249 0 25 Jan 2021
Learning Parametrised Graph Shift Operators George Dasoulas J. Lutzeyer Michalis Vazirgiannis OOD 21 21 0 25 Jan 2021
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks Sergei Ivanov Liudmila Prokhorenkova AI4CE 53 52 0 21 Jan 2021
Directed Acyclic Graph Neural Networks Veronika Thost Jie Chen GNN AI4CE 17 104 0 20 Jan 2021
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses S. Min Kun Wu Sitao Huang Mert Hidayetouglu Jinjun Xiong Eiman Ebrahimi Deming Chen Wen-mei W. Hwu GNN AI4CE 34 24 0 20 Jan 2021
Graph Networks with Spectral Message Passing Kimberly L. Stachenfeld Jonathan Godwin Peter W. Battaglia 41 12 0 31 Dec 2020
Binary Graph Neural Networks Mehdi Bahri Gaétan Bahl S. Zafeiriou GNN AI4CE 11 49 0 31 Dec 2020
Deep Graph Generators: A Survey Faezeh Faez Yassaman Ommi M. Baghshah Hamid R. Rabiee GNN AI4CE 50 57 0 31 Dec 2020
Adaptive Graph Diffusion Networks Chuxiong Sun Jie Hu Hongming Gu Jinpeng Chen Mingchuan Yang GNN DiffM AI4CE 23 12 0 30 Dec 2020
Motif-Driven Contrastive Learning of Graph Representations Shichang Zhang Ziniu Hu Arjun Subramonian Yizhou Sun SSL 28 8 0 23 Dec 2020
Analyzing the Performance of Graph Neural Networks with Pipe Parallelism M. Dearing Xiaoyang Sean Wang GNN AI4CE 21 3 0 20 Dec 2020
A pipeline for fair comparison of graph neural networks in node classification tasks Wentao Zhao Dalin Zhou X. Qiu Wei Jiang 16 5 0 19 Dec 2020
An Experimental Study of the Transferability of Spectral Graph Networks Axel Nilsson Xavier Bresson 25 3 0 18 Dec 2020
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 25 116 0 16 Dec 2020
Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification Deli Chen Yankai Lin Lei Li Xuancheng Ren Peng Li Jie Zhou Xu Sun 32 5 0 14 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 101 1,377 0 14 Dec 2020
Breaking the Expressive Bottlenecks of Graph Neural Networks Mingqi Yang Yanming Shen Heng Qi Baocai Yin 30 10 0 14 Dec 2020
LCS Graph Kernel Based on Wasserstein Distance in Longest Common Subsequence Metric Space Jianming Huang Zhongxi Fang Hiroyuki Kasai 23 19 0 07 Dec 2020
Deep Graph Neural Networks with Shallow Subgraph Samplers Hanqing Zeng Muhan Zhang Yinglong Xia Ajitesh Srivastava Andrey Malevich Rajgopal Kannan Viktor Prasanna Long Jin Ren Chen GNN 14 24 0 02 Dec 2020
Graph convolutions that can finally model local structure Rémy Brossard Oriel Frigo David Dehaene GNN 37 48 0 30 Nov 2020
Graph Signal Recovery Using Restricted Boltzmann Machines Ankith Mohan A. Nakano Emilio Ferrara 17 4 0 20 Nov 2020
Scalable Graph Neural Networks for Heterogeneous Graphs Lingfan Yu Jiajun Shen Jinyang Li Adam Lerer GNN 38 49 0 19 Nov 2020
Design Space for Graph Neural Networks Jiaxuan You Rex Ying J. Leskovec GNN AI4CE 33 315 0 17 Nov 2020
Graph Kernels: State-of-the-Art and Future Challenges Karsten M. Borgwardt Elisabetta Ghisu Felipe Llinares-López Leslie O’Bray Bastian Alexander Rieck AI4TS 31 103 0 07 Nov 2020
PairRE: Knowledge Graph Embeddings via Paired Relation Vectors Linlin Chao Jianshan He Taifeng Wang Wei Chu 13 161 0 07 Nov 2020
On Self-Distilling Graph Neural Network Y. Chen Yatao Bian Xi Xiao Yu Rong Tingyang Xu Junzhou Huang FedML 19 48 0 04 Nov 2020
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning Muhan Zhang Pan Li Yinglong Xia Kai Wang Long Jin 19 186 0 30 Oct 2020
GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs Hao Xu Shengqi Sang Peizhen Bai Laurence Yang Haiping Lu GNN 21 15 0 29 Oct 2020
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 25 283 0 27 Oct 2020
Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method Fuli Feng Weiran Huang Xiangnan He Xin Xin Qifan Wang Tat-Seng Chua GNN CML 23 63 0 22 Oct 2020
Joint Use of Node Attributes and Proximity for Semi-Supervised Classification on Graphs Arpit Merchant M. Mathioudakis 15 1 0 22 Oct 2020
Rethinking pooling in graph neural networks Diego Mesquita Amauri Souza Samuel Kaski GNN AI4CE 20 116 0 22 Oct 2020
Density of States Graph Kernels Leo Huang A. Graven D. Bindel 14 7 0 21 Oct 2020
Robust Optimization as Data Augmentation for Large-scale Graphs Kezhi Kong Ge Li Mucong Ding Zuxuan Wu Chen Zhu Guohao Li Gavin Taylor Tom Goldstein 106 74 0 19 Oct 2020
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 172 123 0 17 Oct 2020
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs Da Zheng Chao Ma Minjie Wang Jinjing Zhou Qidong Su Xiang Song Quan Gan Zheng-Wei Zhang George Karypis FedML GNN 24 243 0 11 Oct 2020