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2102.06555
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Online Graph Dictionary Learning
International Conference on Machine Learning (ICML), 2021
12 February 2021
Cédric Vincent-Cuaz
Titouan Vayer
Rémi Flamary
Marco Corneli
Nicolas Courty
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Papers citing
"Online Graph Dictionary Learning"
26 / 26 papers shown
Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics
Zhichen Zeng
Ruizhong Qiu
Wenxuan Bao
Tianxin Wei
Xiao Lin
Yuchen Yan
Tarek Abdelzaher
Jiawei Han
Hanghang Tong
OOD
AI4CE
494
17
0
19 May 2025
Topological Dictionary Learning
Enrico Grimaldi
Claudio Battiloro
Paolo Di Lorenzo
154
3
0
14 Mar 2025
Gradual Domain Adaptation for Graph Learning
Pui Ieng Lei
Ximing Chen
Yijun Sheng
Yanyan Liu
J. Guo
Zhiguo Gong
OOD
596
1
0
29 Jan 2025
Graph Classification via Reference Distribution Learning: Theory and Practice
Neural Information Processing Systems (NeurIPS), 2024
Zixiao Wang
Jicong Fan
256
10
0
21 Aug 2024
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
D. M. Nguyen
Nina Lukashina
Tai Nguyen
An T. Le
TrungTin Nguyen
Nhat Ho
Jan Peters
Daniel Sonntag
Viktor Zaverkin
Mathias Niepert
285
8
0
03 Feb 2024
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein
Hugues van Assel
Cédric Vincent-Cuaz
Nicolas Courty
Rémi Flamary
Pascal Frossard
Titouan Vayer
423
13
0
03 Feb 2024
Semidefinite Relaxations of the Gromov-Wasserstein Distance
Junyu Chen
Binh T. Nguyen
Yong Sheng Soh
OT
246
8
0
22 Dec 2023
A Quasi-Wasserstein Loss for Learning Graph Neural Networks
The Web Conference (WWW), 2023
Minjie Cheng
Hongteng Xu
463
2
0
18 Oct 2023
Hierarchical Multi-Marginal Optimal Transport for Network Alignment
AAAI Conference on Artificial Intelligence (AAAI), 2023
Zhichen Zeng
Boxin Du
Si Zhang
Yinglong Xia
Zhining Liu
Hanghang Tong
OT
437
38
0
06 Oct 2023
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein
Hugues van Assel
Cédric Vincent-Cuaz
Titouan Vayer
Rémi Flamary
Nicolas Courty
268
0
0
05 Oct 2023
Exploiting Edge Features in Graphs with Fused Network Gromov-Wasserstein Distance
Junjie Yang
Matthieu Labeau
Steeven Villa
OT
243
1
0
28 Sep 2023
Recent Advances in Optimal Transport for Machine Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Eduardo Fernandes Montesuma
Fred-Maurice Ngole-Mboula
Antoine Souloumiac
OOD
OT
331
84
0
28 Jun 2023
Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications
Neural Information Processing Systems (NeurIPS), 2023
Xinyu Ma
Xu Chu
Yasha Wang
Yang Lin
Junfeng Zhao
Liantao Ma
Wenwu Zhu
292
19
0
28 Jun 2023
Structure-Sensitive Graph Dictionary Embedding for Graph Classification
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2023
Guangyi Liu
Tong Zhang
Xudong Wang
Wenting Zhao
Chuanwei Zhou
Zhen Cui
171
2
0
18 Jun 2023
A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
International Conference on Learning Representations (ICLR), 2023
Jiajin Li
Jianheng Tang
Lemin Kong
Huikang Liu
Jia Li
Anthony Man-Cho So
Jose H. Blanchet
266
15
0
12 Mar 2023
Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem
Xavier Aramayo Carrasco
Maksim Nekrashevich
Petr Mokrov
Evgeny Burnaev
Alexander Korotin
OT
672
7
0
10 Mar 2023
Distances for Markov Chains, and Their Differentiation
International Conference on Algorithmic Learning Theory (ALT), 2023
Tristan Brugere
Qingsong Wang
Yusu Wang
OT
OOD
264
5
0
16 Feb 2023
Outlier-Robust Gromov-Wasserstein for Graph Data
Neural Information Processing Systems (NeurIPS), 2023
Lemin Kong
Jiajin Li
Jianheng Tang
Anthony Man-Cho So
298
9
0
09 Feb 2023
Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport
IEEE International Conference on Data Engineering (ICDE), 2023
Jianheng Tang
Yongzi Yu
Jiajin Li
Kangfei Zhao
Fugee Tsung
Jia Li
OT
288
29
0
30 Jan 2023
Implicit Graphon Neural Representation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Xinyue Xia
Zhengchao Wan
Yusu Wang
GNN
AI4CE
445
17
0
07 Nov 2022
Template based Graph Neural Network with Optimal Transport Distances
Neural Information Processing Systems (NeurIPS), 2022
Cédric Vincent-Cuaz
Rémi Flamary
Marco Corneli
Titouan Vayer
Nicolas Courty
OT
249
28
0
31 May 2022
Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Data
Jiajin Li
Jianheng Tang
Lemin Kong
Huikang Liu
Jia Li
Anthony Man-Cho So
Jose H. Blanchet
274
3
0
17 May 2022
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters
International Conference on Machine Learning (ICML), 2022
Luc Brogat-Motte
Rémi Flamary
Céline Brouard
Juho Rousu
Florence dÁlché-Buc
278
27
0
08 Feb 2022
Semi-relaxed Gromov-Wasserstein divergence with applications on graphs
Cédric Vincent-Cuaz
Rémi Flamary
Marco Corneli
Titouan Vayer
Nicolas Courty
OT
468
26
0
06 Oct 2021
Partition and Code: learning how to compress graphs
Giorgos Bouritsas
Andreas Loukas
Nikolaos Karalias
M. Bronstein
338
21
0
05 Jul 2021
Learning Graphon Autoencoders for Generative Graph Modeling
Hongteng Xu
P. Zhao
Junzhou Huang
Dixin Luo
GNN
191
5
0
29 May 2021
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