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

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

11 August 2020
Shyam A. Tailor
Javier Fernandez-Marques
Nicholas D. Lane
    GNN
    MQ
ArXivPDFHTML

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

25 / 25 papers shown
Title
Diffusion Model Quantization: A Review
Diffusion Model Quantization: A Review
Qian Zeng
Chenggong Hu
Mingli Song
Jie Song
MQ
41
0
0
08 May 2025
Inference-friendly Graph Compression for Graph Neural Networks
Inference-friendly Graph Compression for Graph Neural Networks
Yangxin Fan
Haolai Che
Yinghui Wu
GNN
51
0
0
17 Apr 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs
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
43
0
0
30 Dec 2024
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance
Jaskirat Singh
Bram Adams
Ahmed E. Hassan
VLM
29
0
0
01 Nov 2024
On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance
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
32
3
0
25 Mar 2024
Better Schedules for Low Precision Training of Deep Neural Networks
Better Schedules for Low Precision Training of Deep Neural Networks
Cameron R. Wolfe
Anastasios Kyrillidis
35
1
0
04 Mar 2024
Low-bit Quantization for Deep Graph Neural Networks with
  Smoothness-aware Message Propagation
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation
Shuang Wang
B. Eravcı
Rustam Guliyev
Hakan Ferhatosmanoglu
GNN
MQ
19
5
0
29 Aug 2023
Frameless Graph Knowledge Distillation
Frameless Graph Knowledge Distillation
Dai Shi
Zhiqi Shao
Yi Guo
Junbin Gao
21
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
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
31
23
0
23 May 2023
Patch-wise Mixed-Precision Quantization of Vision Transformer
Patch-wise Mixed-Precision Quantization of Vision Transformer
Junrui Xiao
Zhikai Li
Lianwei Yang
Qingyi Gu
MQ
22
12
0
11 May 2023
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless
  Setups
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups
Ioannis Arapakis
P. Papadopoulos
Kleomenis Katevas
Diego Perino
11
7
0
26 Feb 2023
ACQ: Improving Generative Data-free Quantization Via Attention
  Correction
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
20
4
0
18 Jan 2023
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP
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
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang
Bang Wu
Xingliang Yuan
Shirui Pan
Hanghang Tong
Jian Pei
41
98
0
16 May 2022
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
Sung Une Lee
Boming Xia
Yongan Zhang
Ang Li
Yingyan Lin
GNN
47
47
0
22 Dec 2021
QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core
QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core
Yuke Wang
Boyuan Feng
Yufei Ding
GNN
22
39
0
18 Nov 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using
  Vector Quantization
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
25
46
0
27 Oct 2021
Graph-less Neural Networks: Teaching Old MLPs New Tricks via
  Distillation
Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation
Shichang Zhang
Yozen Liu
Yizhou Sun
Neil Shah
20
172
0
17 Oct 2021
Federated Graph Learning -- A Position Paper
Federated Graph Learning -- A Position Paper
Hu Zhang
T. Shen
Fei Wu
Mingyang Yin
Hongxia Yang
Chao Wu
FedML
6
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
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
33
30
0
01 Mar 2021
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
178
1,018
0
06 Mar 2020
Benchmarking Graph Neural Networks
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
183
907
0
02 Mar 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
219
1,329
0
12 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning
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
159
1,748
0
02 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
234
1,801
0
25 Nov 2016
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