Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods

8 November 2021

Papers citing "Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods"

46 / 46 papers shown

Title
FairACE: Achieving Degree Fairness in Graph Neural Networks via Contrastive and Adversarial Group-Balanced Training J. Liu Xiaoqian Jiang X. Li Bohan Zhang J. Zhang 32 0 0 12 Apr 2025
Effects of Random Edge-Dropping on Over-Squashing in Graph Neural Networks Jasraj Singh Keyue Jiang Brooks Paige Laura Toni 59 1 0 11 Feb 2025
Norm Augmented Graph AutoEncoders for Link Prediction Yunhui Liu Huaisong Zhang Xinyi Gao Liuye Guo Zhen Tao Tieke He 38 0 0 09 Feb 2025
Training MLPs on Graphs without Supervision Zehong Wang Zheyuan Zhang Chuxu Zhang Yanfang Ye 59 5 0 05 Dec 2024
SPARC: Spectral Architectures Tackling the Cold-Start Problem in Graph Learning Yahel Jacobs Reut Dayan Uri Shaham 39 0 0 03 Nov 2024
Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement Yakun Wang Daixin Wang Hongrui Liu Bin Hu Yingcui Yan Qiyang Zhang Zhiqiang Zhang 20 6 0 30 Jul 2024
HyperAggregation: Aggregating over Graph Edges with Hypernetworks N. Lell A. Scherp GNN 35 0 0 16 Jul 2024
Graph Knowledge Distillation to Mixture of Experts P. Rumiantsev Mark Coates 18 0 0 17 Jun 2024
GraphStorm: all-in-one graph machine learning framework for industry applications Da Zheng Xiang Song Qi Zhu Jian Zhang Theodore Vasiloudis ... Qingjun Cui Huzefa Rangwala Belinda Zeng Christos Faloutsos George Karypis AI4TS AI4CE VLM 32 4 0 10 Jun 2024
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning Junjie Xu Zongyu Wu Min Lin Xiang Zhang Suhang Wang 30 11 0 03 Jun 2024
Node Duplication Improves Cold-start Link Prediction Zhichun Guo Tong Zhao Yozen Liu Kaiwen Dong William Shiao Neil Shah Nitesh V. Chawla AI4CE 15 3 0 15 Feb 2024
Propagate & Distill: Towards Effective Graph Learners Using Propagation-Embracing MLPs Yong-Min Shin Won-Yong Shin 15 1 0 29 Nov 2023
Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs Yong-Min Shin Won-Yong Shin 11 1 0 20 Nov 2023
Unleashing the potential of GNNs via Bi-directional Knowledge Transfer Shuai Zheng Zhizhe Liu Zhenfeng Zhu Xingxing Zhang Jianxin Li Yao-Min Zhao 25 0 0 26 Oct 2023
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation Mingxuan Ju Tong Zhao Wenhao Yu Neil Shah Yanfang Ye 23 12 0 01 Oct 2023
A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions Zemin Liu Yuan N. Li Nan-Fang Chen Qian Wang Bryan Hooi Bin He FaML 11 12 0 26 Aug 2023
SAILOR: Structural Augmentation Based Tail Node Representation Learning Jie Liao Jintang Li Liang Chen Bing Wu Yatao Bian Zibin Zheng 17 3 0 13 Aug 2023
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs Ling Yang Ye Tian Minkai Xu Zhongyi Liu Shenda Hong Wei Qu Wentao Zhang Bin Cui Muhan Zhang J. Leskovec 19 13 0 04 Aug 2023
Collaborative Graph Neural Networks for Attributed Network Embedding Qiaoyu Tan Xin Zhang Xiao Shi Huang Haojun Chen Jundong Li Xia Hu 22 11 0 22 Jul 2023
Shared Growth of Graph Neural Networks via Prompted Free-direction Knowledge Distillation Kaituo Feng Yikun Miao Changsheng Li Ye Yuan Guoren Wang 18 0 0 02 Jul 2023
Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation Yuwei Cao Liangwei Yang Chen Wang Zhiwei Liu Hao Peng Chenyu You Philip S. Yu 13 21 0 26 Jun 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware Shichang Zhang Atefeh Sohrabizadeh Cheng Wan Zijie Huang Ziniu Hu Yewen Wang Yingyan Lin Lin Jason Cong Yizhou Sun GNN AI4CE 29 22 0 24 Jun 2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication A. Jaiswal Shiwei Liu Tianlong Chen Ying Ding Zhangyang Wang GNN 31 5 0 18 Jun 2023
Graph Entropy Minimization for Semi-supervised Node Classification Yi Luo Guangchun Luo Ke Qin Aiguo Chen 20 0 0 31 May 2023
Modeling Dynamic Environments with Scene Graph Memory Andrey Kurenkov Michael Lingelbach Tanmay Agarwal Emily Jin Chengshu Li Ruohan Zhang Li Fei-Fei Jiajun Wu Silvio Savarese Roberto Martín-Martín 24 11 0 27 May 2023
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs Costas Mavromatis V. Ioannidis Shen Wang Da Zheng Soji Adeshina Jun Ma Han Zhao Christos Faloutsos George Karypis 11 29 0 20 Apr 2023
Graph Collaborative Signals Denoising and Augmentation for Recommendation Ziwei Fan Ke Xu Zhang Dong Hao Peng Jiawei Zhang Philip S. Yu 27 40 0 06 Apr 2023
Structural Imbalance Aware Graph Augmentation Learning Zulong Liu Kejia Chen Zheng Liu 21 0 0 24 Mar 2023
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction Wenqing Zheng E-Wen Huang Nikhil S. Rao Zhangyang Wang Karthik Subbian 18 4 0 27 Feb 2023
Graph-based Knowledge Distillation: A survey and experimental evaluation Jing Liu Tongya Zheng Guanzheng Zhang Qinfen Hao 17 8 0 27 Feb 2023
Knowledge Distillation on Graphs: A Survey Yijun Tian Shichao Pei Xiangliang Zhang Chuxu Zhang Nitesh V. Chawla 10 28 0 01 Feb 2023
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization Hengrui Zhang Shen Wang V. Ioannidis Soji Adeshina Jiani Zhang Xiao Qin Christos Faloutsos Da Zheng George Karypis Philip S. Yu 24 2 0 31 Jan 2023
GLINKX: A Scalable Unified Framework For Homophilous and Heterophilous Graphs Marios Papachristou Rishab Goel Frank Portman M. Miller Rong Jin 10 0 0 01 Nov 2022
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks Weihua Hu Kaidi Cao Kexin Huang E-Wen Huang Karthik Subbian Kenji Kawaguchi J. Leskovec 22 0 0 26 Oct 2022
Symbolic Distillation for Learned TCP Congestion Control S. Sharan Wenqing Zheng Kuo-Feng Hsu Jiarong Xing Ang Chen Zhangyang Wang 10 5 0 24 Oct 2022
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP Jie Chen Shouzhen Chen Mingyuan Bai Junbin Gao Junping Zhang Jian Pu 24 10 0 18 Oct 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again Ajay Jaiswal Peihao Wang Tianlong Chen Justin F. Rousseau Ying Ding Zhangyang Wang 14 10 0 14 Oct 2022
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan Zirui Liu Peihao Wang Wenqing Zheng Kaixiong Zhou Tianlong Chen Xia Hu Zhangyang Wang GNN 15 57 0 14 Oct 2022
Boosting Graph Neural Networks via Adaptive Knowledge Distillation Zhichun Guo Chunhui Zhang Yujie Fan Yijun Tian Chuxu Zhang Nitesh V. Chawla 13 32 0 12 Oct 2022
Linkless Link Prediction via Relational Distillation Zhichun Guo William Shiao Shichang Zhang Yozen Liu Nitesh V. Chawla Neil Shah Tong Zhao 13 41 0 11 Oct 2022
NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs Yijun Tian Chuxu Zhang Zhichun Guo Xiangliang Zhang Nitesh V. Chawla 29 14 0 22 Aug 2022
Infinite Recommendation Networks: A Data-Centric Approach Noveen Sachdeva Mehak Preet Dhaliwal Carole-Jean Wu Julian McAuley DD 26 28 0 03 Jun 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 27 18 0 13 Mar 2022
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Tianlong Chen Kaixiong Zhou Keyu Duan Wenqing Zheng Peihao Wang Xia Hu Zhangyang Wang AAML GNN 19 61 0 24 Aug 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 167 1,058 0 13 Feb 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 226 1,935 0 09 Jun 2018