Degree-Quant: Quantization-Aware Training for Graph Neural Networks

11 August 2020

Shyam A. Tailor

Javier Fernandez-Marques

Nicholas D. Lane

GNN

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Papers citing "Degree-Quant: Quantization-Aware Training for Graph Neural Networks"

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Title
Fast RoPE Attention: Combining the Polynomial Method and Fast Fourier Transform Josh Alman Zhao Song 12 0 0 17 May 2025
Diffusion Model Quantization: A Review Qian Zeng Chenggong Hu Mingli Song Jie Song MQ 45 0 0 08 May 2025
Inference-friendly Graph Compression for Graph Neural Networks Yangxin Fan Haolai Che Yinghui Wu GNN 62 0 0 17 Apr 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs Yuanchang Zhou Siyu Hu Chen Wang Lin-Wang Wang Guangming Tan Weile Jia AI4CE GNN 54 0 0 30 Dec 2024
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance Jaskirat Singh Bram Adams Ahmed E. Hassan VLM 43 0 0 01 Nov 2024
On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance Jaskirat Singh Emad Fallahzadeh Bram Adams Ahmed E. Hassan MQ 40 3 0 25 Mar 2024
Better Schedules for Low Precision Training of Deep Neural Networks Cameron R. Wolfe Anastasios Kyrillidis 47 1 0 04 Mar 2024
Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework Junxian Li Bin Shi Erfei Cui Hua Wei Qinghua Zheng 49 0 0 02 Mar 2024
Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward Arnav Chavan Raghav Magazine Shubham Kushwaha M. Debbah Deepak Gupta 16 18 0 02 Feb 2024
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation Shuang Wang B. Eravcı Rustam Guliyev Hakan Ferhatosmanoglu GNN MQ 27 6 0 29 Aug 2023
Frameless Graph Knowledge Distillation Dai Shi Zhiqi Shao Yi Guo Junbin Gao 39 4 0 13 Jul 2023
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey Jana Vatter R. Mayer Hans-Arno Jacobsen GNN AI4TS AI4CE 48 23 0 23 May 2023
Patch-wise Mixed-Precision Quantization of Vision Transformer Junrui Xiao Zhikai Li Lianwei Yang Qingyi Gu MQ 32 12 0 11 May 2023
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups Ioannis Arapakis P. Papadopoulos Kleomenis Katevas Diego Perino 24 7 0 26 Feb 2023
ACQ: Improving Generative Data-free Quantization Via Attention Correction Jixing Li Xiaozhou Guo Benzhe Dai Guoliang Gong Min Jin Gang Chen Wenyu Mao Huaxiang Lu MQ 30 4 0 18 Jan 2023
Distributed Graph Neural Network Training: A Survey Yingxia Shao Hongzheng Li Xizhi Gu Hongbo Yin Yawen Li Xupeng Miao Wentao Zhang Bin Cui Lei Chen GNN AI4CE 11 56 0 01 Nov 2022
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP Jie Chen Shouzhen Chen Mingyuan Bai Junbin Gao Junping Zhang Jian Pu 40 10 0 18 Oct 2022
Linkless Link Prediction via Relational Distillation Zhichun Guo William Shiao Shichang Zhang Yozen Liu Nitesh V. Chawla Neil Shah Tong Zhao 24 41 0 11 Oct 2022
Triple Sparsification of Graph Convolutional Networks without Sacrificing the Accuracy Md. Khaledur Rahman A. Azad GNN 45 7 0 06 Aug 2022
BiFeat: Supercharge GNN Training via Graph Feature Quantization Yuxin Ma Ping Gong Jun Yi Z. Yao Cheng-rong Li Yuxiong He Feng Yan GNN 21 6 0 29 Jul 2022
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks Chuang Liu Xueqi Ma Yinbing Zhan Liang Ding Dapeng Tao Bo Du Wenbin Hu Danilo Mandic 42 28 0 18 Jul 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 45 104 0 16 May 2022
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective Xin Liu Yurui Lai Lei Deng Guoqi Li Xiaochun Ye Xiaochun Ye Shirui Pan Yuan Xie GNN 16 42 0 10 Feb 2022
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design Sung Une Lee Boming Xia Yongan Zhang Ang Li Yingyan Lin GNN 55 47 0 22 Dec 2021
QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core Yuke Wang Boyuan Feng Yufei Ding GNN 33 41 0 18 Nov 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding Kezhi Kong Jingling Li Chen Zhu John P. Dickerson Furong Huang Tom Goldstein GNN MQ 33 47 0 27 Oct 2021
Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation Shichang Zhang Yozen Liu Yizhou Sun Neil Shah 33 173 0 17 Oct 2021
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks Moshe Eliasof Ben Bodner Eran Treister GNN 35 7 0 10 Oct 2021
G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency Yongan Zhang Haoran You Yonggan Fu Tong Geng Ang Li Yingyan Lin GNN 21 28 0 18 Sep 2021
Federated Graph Learning -- A Position Paper Hu Zhang T. Shen Fei Wu Mingyang Yin Hongxia Yang Chao Wu FedML 16 49 0 24 May 2021
Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets Haoran You Zhihan Lu Zijian Zhou Y. Fu Yingyan Lin GNN 38 30 0 01 Mar 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 917 0 02 Mar 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,340 0 12 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 231 1,780 0 02 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 254 1,811 0 25 Nov 2016