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Large-scale graph representation learning with very deep GNNs and
  self-supervision

Large-scale graph representation learning with very deep GNNs and self-supervision

20 July 2021
Ravichandra Addanki
Peter W. Battaglia
David Budden
Andreea Deac
Jonathan Godwin
Thomas Keck
Wai Lok Sibon Li
Alvaro Sanchez-Gonzalez
Jacklynn Stott
S. Thakoor
Petar Velivcković
    SSL
    AI4CE
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Papers citing "Large-scale graph representation learning with very deep GNNs and self-supervision"

20 / 20 papers shown
Title
AMR-Transformer: Enabling Efficient Long-range Interaction for Complex Neural Fluid Simulation
Zeyi Xu
Jinfan Liu
Kuangxu Chen
Ye Chen
Zhangli Hu
Bingbing Ni
52
0
0
13 Mar 2025
ASTRA: A Scene-aware TRAnsformer-based model for trajectory prediction
ASTRA: A Scene-aware TRAnsformer-based model for trajectory prediction
Izzeddin Teeti
Aniket Thomas
Munish Monga
S. Kumar
Uddeshya Singh
Andrew Bradley
Biplab Banerjee
Fabio Cuzzolin
38
0
0
20 Jan 2025
A review of graph neural network applications in mechanics-related
  domains
A review of graph neural network applications in mechanics-related domains
Yingxue Zhao
Haoran Li
Haosu Zhou
H. Attar
Tobias Pfaff
Nan Li
AI4CE
29
5
0
10 Jul 2024
Training-free Graph Neural Networks and the Power of Labels as Features
Training-free Graph Neural Networks and the Power of Labels as Features
Ryoma Sato
26
4
0
30 Apr 2024
Graph Neural Networks-based Hybrid Framework For Predicting Particle
  Crushing Strength
Graph Neural Networks-based Hybrid Framework For Predicting Particle Crushing Strength
Tongya Zheng
Tianli Zhang
Qingzheng Guan
Wenjie Huang
Zunlei Feng
Min-Gyoo Song
Chun-Yen Chen
AI4CE
31
1
0
26 Jul 2023
Anticipating Technical Expertise and Capability Evolution in Research
  Communities using Dynamic Graph Transformers
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph Transformers
Sameera Horawalavithana
Ellyn Ayton
A. Usenko
Robin Cosbey
Svitlana Volkova
AI4TS
15
0
0
18 Jul 2023
Evolving Computation Graphs
Evolving Computation Graphs
Andreea Deac
Jian Tang
22
1
0
22 Jun 2023
Extreme Acceleration of Graph Neural Network-based Prediction Models for
  Quantum Chemistry
Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry
Hatem Helal
J. Firoz
Jenna A. Bilbrey
M. M. Krell
Tom Murray
Ang Li
S. Xantheas
Sutanay Choudhury
GNN
31
5
0
25 Nov 2022
Unified 2D and 3D Pre-Training of Molecular Representations
Unified 2D and 3D Pre-Training of Molecular Representations
Jinhua Zhu
Yingce Xia
Lijun Wu
Shufang Xie
Tao Qin
Wen-gang Zhou
Houqiang Li
Tie-Yan Liu
AI4CE
54
67
0
14 Jul 2022
Affinity-Aware Graph Networks
Affinity-Aware Graph Networks
A. Velingker
A. Sinop
Ira Ktena
Petar Velickovic
Sreenivas Gollapudi
GNN
48
16
0
23 Jun 2022
Ordered Subgraph Aggregation Networks
Ordered Subgraph Aggregation Networks
Chao Qian
Gaurav Rattan
Floris Geerts
Christopher Morris
Mathias Niepert
41
56
0
22 Jun 2022
Direct Molecular Conformation Generation
Direct Molecular Conformation Generation
Jinhua Zhu
Yingce Xia
Chang-Shu Liu
Lijun Wu
Shufang Xie
...
Tao Qin
Wen-gang Zhou
Houqiang Li
Haiguang Liu
Tie-Yan Liu
26
41
0
03 Feb 2022
Graph Neural Network Training with Data Tiering
Graph Neural Network Training with Data Tiering
S. Min
Kun Wu
Mert Hidayetoğlu
Jinjun Xiong
Xiang Song
Wen-mei W. Hwu
GNN
17
15
0
10 Nov 2021
On Representation Knowledge Distillation for Graph Neural Networks
On Representation Knowledge Distillation for Graph Neural Networks
Chaitanya K. Joshi
Fayao Liu
Xu Xun
Jie Lin
Chuan-Sheng Foo
19
54
0
09 Nov 2021
Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular
  Graphs
Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs
Zhao Xu
Youzhi Luo
Xuan Zhang
Xinyi Xu
Yaochen Xie
Meng Liu
Kaleb Dickerson
Cheng Deng
Maho Nakata
Shuiwang Ji
33
39
0
30 Sep 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
174
1,104
0
27 Apr 2021
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Hongyu Ren
Maho Nakata
Yuxiao Dong
J. Leskovec
AI4CE
21
398
0
17 Mar 2021
Large-Scale Representation Learning on Graphs via Bootstrapping
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
13
215
0
12 Feb 2021
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric
  graphs
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
P. D. Haan
Maurice Weiler
Taco S. Cohen
Max Welling
100
127
0
11 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
189
914
0
02 Mar 2020
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