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"

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Title
The PWLR Graph Representation: A Persistent Weisfeiler-Lehman scheme with Random Walks for Graph Classification S. Park Y. Choi Dosang Joe U. J. Choi Youngho Woo 25 2 0 29 Aug 2022
Literature Review: Graph Kernels in Chemoinformatics James Young 21 0 0 09 Aug 2022
Wasserstein Graph Distance Based on $L_1$ -Approximated Tree Edit Distance between Weisfeiler-Lehman Subtrees Zhongxi Fang Jianming Huang Xun Su Hiroyuki Kasai 73 8 0 09 Jul 2022
SBERT studies Meaning Representations: Decomposing Sentence Embeddings into Explainable Semantic Features Juri Opitz Anette Frank 96 37 0 14 Jun 2022
Approximate Network Motif Mining Via Graph Learning Carlos Oliver Dexiong Chen Vincent Mallet P. Philippopoulos Karsten Borgwardt 39 4 0 02 Jun 2022
Multi-scale Wasserstein Shortest-path Graph Kernels for Graph Classification Wei Ye Hao Tian Qi Chen 117 2 0 02 Jun 2022
Template based Graph Neural Network with Optimal Transport Distances Cédric Vincent-Cuaz Rémi Flamary Marco Corneli Titouan Vayer Nicolas Courty OT 83 20 0 31 May 2022
Graph-level Neural Networks: Current Progress and Future Directions Ge Zhang Hongzhi Zhang Jian Yang Shan Xue Wenbin Hu Chuan Zhou Hao Peng Quan.Z Sheng Charu C. Aggarwal GNN AI4CE 100 0 0 31 May 2022
Hilbert Curve Projection Distance for Distribution Comparison Tao Li Cheng Meng Hongteng Xu Jun Yu 86 14 0 30 May 2022
On the Convergence of Semi-Relaxed Sinkhorn with Marginal Constraint and OT Distance Gaps Takumi Fukunaga Hiroyuki Kasai OT 134 2 0 27 May 2022
Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited Nils M. Kriege 76 16 0 22 May 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 129 40 0 25 Mar 2022
On a linear fused Gromov-Wasserstein distance for graph structured data Dai Hai Nguyen Koji Tsuda OT 45 13 0 09 Mar 2022
GraphDCA -- a Framework for Node Distribution Comparison in Real and Synthetic Graphs Ciwan Ceylan Petra Poklukar Hanna Hultin Alexander Kravchenko Anastasia Varava Danica Kragic 50 1 0 08 Feb 2022
Weisfeiler-Lehman meets Gromov-Wasserstein Samantha Chen Sunhyuk Lim Facundo Mémoli Qingsong Wang Yusu Wang CoGe 78 18 0 05 Feb 2022
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants Ningyuan Huang Soledad Villar 72 64 0 18 Jan 2022
Weisfeiler and Leman go Machine Learning: The Story so far Christopher Morris Y. Lipman Haggai Maron Bastian Rieck Nils M. Kriege Martin Grohe Matthias Fey Karsten Borgwardt GNN 127 118 0 18 Dec 2021
SLOSH: Set LOcality Sensitive Hashing via Sliced-Wasserstein Embeddings Yuzhe Lu Xinran Liu Andrea Soltoggio Soheil Kolouri 94 8 0 11 Dec 2021
Adversarial Attacks on Graph Classification via Bayesian Optimisation Xingchen Wan Henry Kenlay Binxin Ru Arno Blaas Michael A. Osborne Xiaowen Dong AAML 96 13 0 04 Nov 2021
Topological Relational Learning on Graphs Yuzhou Chen Baris Coskunuzer Yulia R. Gel 73 44 0 29 Oct 2021
Graph Filtration Kernels Till Hendrik Schulz Pascal Welke Stefanie Wrobel 60 13 0 22 Oct 2021
Semi-relaxed Gromov-Wasserstein divergence with applications on graphs Cédric Vincent-Cuaz Rémi Flamary Marco Corneli Titouan Vayer Nicolas Courty OT 91 23 0 06 Oct 2021
Graphon based Clustering and Testing of Networks: Algorithms and Theory Mahalakshmi Sabanayagam L. C. Vankadara Debarghya Ghoshdastidar 89 5 0 06 Oct 2021
A Regularized Wasserstein Framework for Graph Kernels Asiri Wijesinghe Qing Wang Stephen Gould 66 4 0 06 Oct 2021
Weisfeiler-Leman in the BAMBOO: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity Juri Opitz Angel Daza A. Frank 69 31 0 26 Aug 2021
Learning Aesthetic Layouts via Visual Guidance Qingyuan Zheng Zhuoru Li Adam W. Bargteil 52 0 0 13 Jul 2021
Balanced Coarsening for Multilevel Hypergraph Partitioning via Wasserstein Discrepancy Zhicheng Guo Jiaxuan Zhao L. Jiao Xu Liu 64 0 0 14 Jun 2021
Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels Dai Hai Nguyen Canh Hao Nguyen Hiroshi Mamitsuka 56 9 0 08 Jun 2021
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions Leslie O’Bray Max Horn Bastian Rieck Karsten Borgwardt 112 41 0 02 Jun 2021
Graph Similarity Description: How Are These Graphs Similar? Corinna Coupette Jilles Vreeken 55 12 0 29 May 2021
Revisiting 2D Convolutional Neural Networks for Graph-based Applications Yecheng Lyu Xinming Huang Ziming Zhang GNN 67 4 0 23 May 2021
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs Christopher Morris Matthias Fey Nils M. Kriege GNN 55 24 0 12 May 2021
Smart Vectorizations for Single and Multiparameter Persistence Baris Coskunuzer Cüneyt Gürcan Akçora I. Segovia-Dominguez Zhiwei Zhen Murat Kantarcioglu Yulia R. Gel 30 2 0 10 Apr 2021
Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels Qingqing Long Yilun Jin Yi Wu Guojie Song 107 38 0 07 Apr 2021
Set Representation Learning with Generalized Sliced-Wasserstein Embeddings Navid Naderializadeh Soheil Kolouri Joseph F. Comer Reed W. Andrews Heiko Hoffmann 113 6 0 05 Mar 2021
Online Graph Dictionary Learning Cédric Vincent-Cuaz Titouan Vayer Rémi Flamary Marco Corneli Nicolas Courty 72 46 0 12 Feb 2021
A Generalized Weisfeiler-Lehman Graph Kernel T. Schulz Tamás Horváth Pascal Welke Stefan Wrobel 71 30 0 20 Jan 2021
LCS Graph Kernel Based on Wasserstein Distance in Longest Common Subsequence Metric Space Jianming Huang Zhongxi Fang Hiroyuki Kasai 52 20 0 07 Dec 2020
Exploring Deep 3D Spatial Encodings for Large-Scale 3D Scene Understanding Saqib Ali Khan Yilei Shi Muhammad Shahzad Xiaoxiang Zhu 3DPC 3DV 28 0 0 29 Nov 2020
Graph Kernels: State-of-the-Art and Future Challenges Karsten Borgwardt Elisabetta Ghisu Felipe Llinares-López Leslie O’Bray Bastian Rieck AI4TS 99 107 0 07 Nov 2020
Transport based Graph Kernels Kai Ma Peng Wan Daoqiang Zhang OT 23 1 0 02 Nov 2020
Graph embedding using multi-layer adjacent point merging model Jianming Huang Hiroyuki Kasai 22 3 0 28 Oct 2020
Density of States Graph Kernels Leo Huang A. Graven D. Bindel 42 7 0 21 Oct 2020
Provenance Graph Kernel David Kohan Marzagão T. D. Huynh Ayah Helal Sean Baccas Luc Moreau 40 1 0 20 Oct 2020
Towards Expressive Graph Representation Chengsheng Mao Liang Yao Yuan Luo 88 2 0 12 Oct 2020
Ordinal Pattern Kernel for Brain Connectivity Network Classification Kai Ma Biao Jie Daoqiang Zhang 25 0 0 18 Aug 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 272 830 0 16 Jul 2020
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening Louis Bethune Yacouba Kaloga Pierre Borgnat Aurélien Garivier Amaury Habrard 28 3 0 07 Jul 2020
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention Grégoire Mialon Dexiong Chen Alexandre d’Aspremont Julien Mairal OT 42 0 0 22 Jun 2020
Wasserstein Embedding for Graph Learning Soheil Kolouri Navid Naderializadeh Gustavo K. Rohde Heiko Hoffmann GNN 101 89 0 16 Jun 2020