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Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems

Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems

International Conference on Learning Representations (ICLR), 2024
Jie Chen
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Papers citing "Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems"

24 / 24 papers shown
Learning Sparse Approximate Inverse Preconditioners for Conjugate Gradient Solvers on GPUs
Learning Sparse Approximate Inverse Preconditioners for Conjugate Gradient Solvers on GPUs
Zherui Yang
Zhehao Li
Kangbo Lyu
Yixuan Li
Tao Du
Ligang Liu
80
3
0
31 Oct 2025
Fast Linear Solvers via AI-Tuned Markov Chain Monte Carlo-based Matrix Inversion
Fast Linear Solvers via AI-Tuned Markov Chain Monte Carlo-based Matrix Inversion
A. Lebedev
Won Kyung Lee
Soumyadip Ghosh
Olha I. Yaman
V. Kalantzis
Yingdong Lu
T. Nowicki
Shashanka Ubaru
L. Horesh
V. Alexandrov
96
1
0
22 Sep 2025
Preconditioned Deformation Grids
Preconditioned Deformation Grids
Julian Kaltheuner
Alexander Oebel
Hannah Droege
P. Stotko
Reinhard Klein
160
0
0
22 Sep 2025
Matrix-free Neural Preconditioner for the Dirac Operator in Lattice Gauge Theory
Matrix-free Neural Preconditioner for the Dirac Operator in Lattice Gauge Theory
Yixuan Sun
Srinivas Eswar
Y. Lin
William Detmold
P. Shanahan
Xiaoye Li
Yang Liu
Prasanna Balaprakash
AI4CE
145
0
0
12 Sep 2025
Learning incomplete factorization preconditioners for GMRES
Learning incomplete factorization preconditioners for GMRES
Paul Hausner
Aleix Nieto Juscafresa
Jens Sjölund
257
8
0
12 Sep 2024
Neural incomplete factorization: learning preconditioners for the conjugate gradient method
Neural incomplete factorization: learning preconditioners for the conjugate gradient method
Paul Hausner
Ozan Oktem
Jens Sjölund
738
17
0
25 May 2023
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-trainingInternational Conference on Learning Representations (ICLR), 2023
Hong Liu
Zhiyuan Li
David Leo Wright Hall
Abigail Z. Jacobs
Tengyu Ma
VLM
596
221
0
23 May 2023
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and CachingConference on Machine Learning and Systems (MLSys), 2023
Tim Kaler
A. Iliopoulos
P. Murzynowski
Tao B. Schardl
C. E. Leiserson
Jie Chen
GNN
192
23
0
04 May 2023
A Comprehensive Survey of Continual Learning: Theory, Method and Application
A Comprehensive Survey of Continual Learning: Theory, Method and ApplicationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Liyuan Wang
Xingxing Zhang
Hang Su
Jun Zhu
KELMCLL
786
1,089
0
31 Jan 2023
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Tim Kaler
Nickolas Stathas
Anne Ouyang
A. Iliopoulos
Tao B. Schardl
C. E. Leiserson
Jie Chen
GNN
273
62
0
16 Oct 2021
Neural Operator: Learning Maps Between Function Spaces
Neural Operator: Learning Maps Between Function Spaces
Nikola B. Kovachki
Zong-Yi Li
Burigede Liu
Kamyar Azizzadenesheli
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
766
551
0
19 Aug 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential EquationsInternational Conference on Learning Representations (ICLR), 2020
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
1.3K
3,333
0
18 Oct 2020
Simple and Deep Graph Convolutional Networks
Simple and Deep Graph Convolutional Networks
Ming Chen
Zhewei Wei
Zengfeng Huang
Bolin Ding
Yaliang Li
GNN
517
1,786
0
04 Jul 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations
Neural Operator: Graph Kernel Network for Partial Differential EquationsInternational Conference on Learning Representations (ICLR), 2020
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
507
921
0
07 Mar 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operatorsNature Machine Intelligence (NMI), 2019
Lu Lu
Pengzhan Jin
George Karniadakis
1.0K
2,950
0
08 Oct 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
684
3,648
0
19 Feb 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaMLGNNAI4TSAI4CE
1.6K
10,242
0
03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CEGNN
2.2K
6,422
0
20 Dec 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
881
9,024
0
01 Oct 2018
Stochastic Gradient Descent with Biased but Consistent Gradient Estimators
Stochastic Gradient Descent with Biased but Consistent Gradient Estimators
Jie Chen
Ronny Luss
265
46
0
31 Jul 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie Chen
Tengfei Ma
Cao Xiao
GNN
395
1,655
0
30 Jan 2018
Graph Attention Networks
Graph Attention NetworksInternational Conference on Learning Representations (ICLR), 2017
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
3.8K
24,093
0
30 Oct 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large GraphsNeural Information Processing Systems (NeurIPS), 2017
William L. Hamilton
Z. Ying
J. Leskovec
2.5K
18,151
0
07 Jun 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
1.8K
32,963
0
09 Sep 2016