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You Can Have Better Graph Neural Networks by Not Training Weights at
  All: Finding Untrained GNNs Tickets

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets

28 November 2022
Tianjin Huang
Tianlong Chen
Meng Fang
Vlado Menkovski
Jiaxu Zhao
Lu Yin
Yulong Pei
D. Mocanu
Zhangyang Wang
Mykola Pechenizkiy
Shiwei Liu
    GNN
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Papers citing "You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets"

14 / 14 papers shown
Title
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
Danny Wang
Ruihong Qiu
Guangdong Bai
Zi Huang
51
0
0
09 Feb 2025
Link Prediction with Untrained Message Passing Layers
Link Prediction with Untrained Message Passing Layers
Lisi Qarkaxhija
Anatol E. Wegner
Ingo Scholtes
20
0
0
24 Jun 2024
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at
  Initialization
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at Initialization
Avrajit Ghosh
Xitong Zhang
Kenneth K. Sun
Qing Qu
S. Ravishankar
Rongrong Wang
MedIm
16
5
0
07 Jun 2024
Graph Neural Networks Do Not Always Oversmooth
Graph Neural Networks Do Not Always Oversmooth
Bastian Epping
Alexandre René
M. Helias
Michael T. Schaub
25
3
0
04 Jun 2024
You do not have to train Graph Neural Networks at all on text-attributed
  graphs
You do not have to train Graph Neural Networks at all on text-attributed graphs
Kaiwen Dong
Zhichun Guo
Nitesh V. Chawla
19
1
0
17 Apr 2024
Future Directions in the Theory of Graph Machine Learning
Future Directions in the Theory of Graph Machine Learning
Christopher Morris
Fabrizio Frasca
Nadav Dym
Haggai Maron
.Ismail .Ilkan Ceylan
Ron Levie
Derek Lim
Michael M. Bronstein
Martin Grohe
Stefanie Jegelka
AI4CE
27
4
0
03 Feb 2024
Multicoated and Folded Graph Neural Networks with Strong Lottery Tickets
Multicoated and Folded Graph Neural Networks with Strong Lottery Tickets
Jiale Yan
Hiroaki Ito
Ángel López García-Arias
Yasuyuki Okoshi
Hikari Otsuka
Kazushi Kawamura
Thiem Van Chu
Masato Motomura
25
1
0
06 Dec 2023
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs
Yu-xin Zhang
Lirui Zhao
Mingbao Lin
Yunyun Sun
Yiwu Yao
Xingjia Han
Jared Tanner
Shiwei Liu
Rongrong Ji
SyDa
24
40
0
13 Oct 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
11
6
0
05 Aug 2023
Correlation-aware Spatial-Temporal Graph Learning for Multivariate
  Time-series Anomaly Detection
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection
Yu Zheng
Huan Yee Koh
Ming Jin
Lianhua Chi
Khoa T. Phan
Shirui Pan
Yi-Ping Phoebe Chen
Wei Xiang
AI4TS
8
24
0
17 Jul 2023
Evaluating Self-Supervised Learning for Molecular Graph Embeddings
Evaluating Self-Supervised Learning for Molecular Graph Embeddings
Hanchen Wang
Jean Kaddour
Shengchao Liu
Jian Tang
Joan Lasenby
Qi Liu
14
20
0
16 Jun 2022
Geom-GCN: Geometric Graph Convolutional Networks
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
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
226
1,726
0
09 Jun 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
154
1,748
0
02 Mar 2017
1