v1v2 (latest)

Wasserstein Weisfeiler-Lehman Graph Kernels

4 June 2019

Matteo Togninalli

M. Ghisu

Felipe Llinares-López

Bastian Rieck

Karsten Borgwardt

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Papers citing "Wasserstein Weisfeiler-Lehman Graph Kernels"

50 / 109 papers shown

Title
Constrained Sliced Wasserstein Embedding Navid Naderializadeh Darian Salehi Xinran Liu Soheil Kolouri 34 0 0 02 Jun 2025
WILTing Trees: Interpreting the Distance Between MPNN Embeddings Masahiro Negishi Thomas Gärtner Pascal Welke OT 26 0 0 30 May 2025
Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks Han Zhang Yan Wang Guanfeng Liu Pengfei Ding Huaxiong Wang Kwok-Yan Lam 96 0 0 20 May 2025
Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings Adrien Lagesse Marc Lelarge 74 0 0 19 May 2025
Metric Graph Kernels via the Tropical Torelli Map Yueqi Cao Anthea Monod 42 0 0 17 May 2025
Transition States Energies from Machine Learning: An Application to Reverse Water-Gas Shift on Single-Atom Alloys Raffaele Cheula Mie Andersen 109 0 0 01 May 2025
Network Embedding Exploration Tool (NEExT) Ashkan Dehghan P. Prałat F. Théberge GNN 81 0 0 20 Mar 2025
Wasserstein-based Kernels for Clustering: Application to Power Distribution Graphs Alfredo Oneto B. Gjorgiev G. Sansavini 132 0 0 18 Mar 2025
Graph Learning for Numeric Planning Dillon Z. Chen Sylvie Thiébaux 106 0 0 08 Jan 2025
WLPlan: Relational Features for Symbolic Planning Dillon Z. Chen 93 0 0 01 Nov 2024
Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks Xuyuan Liu Yinghao Cai Qihui Yang Yujun Yan 85 1 0 31 Oct 2024
Learning signals defined on graphs with optimal transport and Gaussian process regression Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 210 1 0 21 Oct 2024
Querying functional and structural niches on spatial transcriptomics data Mo Chen Minsheng Hao Xinquan Liu Lin Deng Chen Li Dongfang Wang Kui Hua Xuegong Zhang Lei Wei 68 0 0 14 Oct 2024
GraphIC: A Graph-Based In-Context Example Retrieval Model for Multi-Step Reasoning Jiale Fu Yaqing Wang Simeng Han Jiaming Fan Chen Si 142 1 0 03 Oct 2024
TopER: Topological Embeddings in Graph Representation Learning Astrit Tola Funmilola Mary Taiwo Cüneyt Gürcan Akçora Baris Coskunuzer 61 0 0 02 Oct 2024
Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuation Ali Falahati Mohammad Mohammadi Amiri 29 1 0 22 Aug 2024
Graph Classification via Reference Distribution Learning: Theory and Practice Zixiao Wang Jicong Fan 55 0 0 21 Aug 2024
Improving the Expressiveness of $K$ -hop Message-Passing GNNs by Injecting Contextualized Substructure Information Tianjun Yao Yiongxu Wang Kun Zhang Shangsong Liang 95 11 0 27 Jun 2024
Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks S. S. Shuvo Ali Aghdaei Zhuo Feng 80 0 0 15 Jun 2024
Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective De Li Xianxian Li Zeming Gan Qiyu Li Bin Qu Jinyan Wang NoLa 70 2 0 11 Jun 2024
Deep Hierarchical Graph Alignment Kernels Shuhao Tang Hao Tian Xiaofeng Cao Wei Ye 85 1 0 09 May 2024
Improving Graph Machine Learning Performance Through Feature Augmentation Based on Network Control Theory Anwar Said O. Ahmad W. Abbas Mudassir Shabbir X. Koutsoukos 55 3 0 03 May 2024
Semi-Supervised Image Captioning Considering Wasserstein Graph Matching Yang Yang 87 0 0 26 Mar 2024
AKBR: Learning Adaptive Kernel-based Representations for Graph Classification Feifei Qian Lixin Cui Yue Wang Hangyuan Du Lu Bai Edwin R. Hancock 52 0 0 24 Mar 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 107 6 0 06 Feb 2024
Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery Pengwei Yan Kaisong Song Zhuoren Jiang Yangyang Kang Tianqianjin Lin Changlong Sun Xiaozhong Liu AI4CE 57 3 0 19 Dec 2023
Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs Xingtong Yu Zhenghao Liu Yuan Fang Zemin Liu Sihong Chen Xinming Zhang 127 31 0 26 Nov 2023
Optimal Transport with Cyclic Symmetry Shoichiro Takeda Yasunori Akagi Naoki Marumo Kenta Niwa 25 0 0 22 Nov 2023
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning Pascal Klink Carlo DÉramo Jan Peters Joni Pajarinen 76 3 0 25 Sep 2023
Filtration Surfaces for Dynamic Graph Classification Franz Srambical Bastian Rieck 61 1 0 07 Sep 2023
Fast Optimal Transport through Sliced Wasserstein Generalized Geodesics Guillaume Mahey Laetitia Chapel Gilles Gasso Clément Bonet Nicolas Courty OT 47 4 0 04 Jul 2023
Structure-Sensitive Graph Dictionary Embedding for Graph Classification Guangyi Liu Tong Zhang Xudong Wang Wenting Zhao Chuanwei Zhou Zhen Cui 61 1 0 18 Jun 2023
Fisher Information Embedding for Node and Graph Learning Dexiong Chen Paolo Pellizzoni Karsten Borgwardt GNN 61 2 0 12 May 2023
SMATCH++: Standardized and Extended Evaluation of Semantic Graphs Juri Opitz 58 23 0 11 May 2023
AERK: Aligned Entropic Reproducing Kernels through Continuous-time Quantum Walks Lixin Cui Ming Li Yue Wang Lu Bai Edwin R. Hancock 119 0 0 04 Mar 2023
Distances for Markov Chains, and Their Differentiation Tristan Brugere Qingsong Wang Yusu Wang OT OOD 60 4 0 16 Feb 2023
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks Zemin Liu Xingtong Yu Yuan Fang Xinming Zhang LLMAG AI4CE 102 146 0 16 Feb 2023
Deep Graph-Level Clustering Using Pseudo-Label-Guided Mutual Information Maximization Network Jinyu Cai Yi Han Wenzhong Guo Jicong Fan 87 9 0 05 Feb 2023
The Weisfeiler-Lehman Distance: Reinterpretation and Connection with GNNs Samantha Chen Sunhyuk Lim Facundo Mémoli Qingsong Wang Yusu Wang 59 8 0 01 Feb 2023
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification Sonny Achten F. Tonin Panagiotis Patrinos Johan A. K. Suykens 88 4 0 31 Jan 2023
Curvature Filtrations for Graph Generative Model Evaluation Joshua Southern Jeremy Wayland Michael M. Bronstein Bastian Rieck 82 17 0 30 Jan 2023
Subgraph Centralization: A Necessary Step for Graph Anomaly Detection Zhuang Zhong Kai Ming Ting Guansong Pang Shuaibin Song 69 8 0 17 Jan 2023
QESK: Quantum-based Entropic Subtree Kernels for Graph Classification Lu Bai Lixin Cui Edwin R. Hancock 64 0 0 10 Dec 2022
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification Lu Bai Lixin Cui Yue Wang Ming Li Edwin R. Hancock 71 50 0 05 Nov 2022
Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations Giannis Nikolentzos Michail Chatzianastasis Michalis Vazirgiannis 53 8 0 04 Nov 2022
Better Smatch = Better Parser? AMR evaluation is not so simple anymore Juri Opitz Anette Frank 69 15 0 12 Oct 2022
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks Ching-Yao Chuang Stefanie Jegelka OOD 116 38 0 04 Oct 2022
Metric Distribution to Vector: Constructing Data Representation via Broad-Scale Discrepancies Xue Liu Dan Sun X. Cao Hao Ye Wei Wei 71 0 0 02 Oct 2022
A Simple Way to Learn Metrics Between Attributed Graphs Yacouba Kaloga Pierre Borgnat Amaury Habrard GNN 61 1 0 26 Sep 2022
Gradual Weisfeiler-Leman: Slow and Steady Wins the Race Franka Bause Nils M. Kriege CLL 79 6 0 19 Sep 2022