ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2101.08104
  4. Cited By
A Generalized Weisfeiler-Lehman Graph Kernel

A Generalized Weisfeiler-Lehman Graph Kernel

20 January 2021
T. Schulz
Tamás Horváth
Pascal Welke
Stefan Wrobel
ArXivPDFHTML

Papers citing "A Generalized Weisfeiler-Lehman Graph Kernel"

13 / 13 papers shown
Title
TUDataset: A collection of benchmark datasets for learning with graphs
TUDataset: A collection of benchmark datasets for learning with graphs
Christopher Morris
Nils M. Kriege
Franka Bause
Kristian Kersting
Petra Mutzel
Marion Neumann
230
819
0
16 Jul 2020
Theoretically Expressive and Edge-aware Graph Learning
Theoretically Expressive and Edge-aware Graph Learning
Federico Errica
D. Bacciu
Alessio Micheli
31
6
0
24 Jan 2020
Wasserstein Weisfeiler-Lehman Graph Kernels
Wasserstein Weisfeiler-Lehman Graph Kernels
Matteo Togninalli
M. Ghisu
Felipe Llinares-López
Bastian Rieck
Karsten Borgwardt
58
199
0
04 Jun 2019
On the equivalence between graph isomorphism testing and function
  approximation with GNNs
On the equivalence between graph isomorphism testing and function approximation with GNNs
Zhengdao Chen
Soledad Villar
Lei Chen
Joan Bruna
81
281
0
29 May 2019
DDGK: Learning Graph Representations for Deep Divergence Graph Kernels
DDGK: Learning Graph Representations for Deep Divergence Graph Kernels
Rami Al-Rfou
Dustin Zelle
Bryan Perozzi
46
57
0
21 Apr 2019
A Survey on Graph Kernels
A Survey on Graph Kernels
Nils M. Kriege
Fredrik D. Johansson
Christopher Morris
125
418
0
28 Mar 2019
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris
Martin Ritzert
Matthias Fey
William L. Hamilton
J. E. Lenssen
Gaurav Rattan
Martin Grohe
GNN
189
1,634
0
04 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
232
7,638
0
01 Oct 2018
GraKeL: A Graph Kernel Library in Python
GraKeL: A Graph Kernel Library in Python
Giannis Siglidis
Giannis Nikolentzos
Stratis Limnios
C. Giatsidis
Konstantinos Skianis
Michalis Vazirgiannis
GP
38
158
0
06 Jun 2018
On Valid Optimal Assignment Kernels and Applications to Graph
  Classification
On Valid Optimal Assignment Kernels and Applications to Graph Classification
Nils M. Kriege
Pierre-Louis Giscard
Richard C. Wilson
84
215
0
03 Jun 2016
Fast Computation of Wasserstein Barycenters
Fast Computation of Wasserstein Barycenters
Marco Cuturi
Arnaud Doucet
OT
86
740
0
16 Oct 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation
  Distances
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
209
4,258
0
04 Jun 2013
Dynamic Clustering of Histogram Data Based on Adaptive Squared
  Wasserstein Distances
Dynamic Clustering of Histogram Data Based on Adaptive Squared Wasserstein Distances
A. Irpino
R. Verde
F. D. Carvalho
47
53
0
07 Oct 2011
1