Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2106.12575
Cited By
Weisfeiler and Lehman Go Cellular: CW Networks
23 June 2021
Cristian Bodnar
Fabrizio Frasca
N. Otter
Yu Guang Wang
Pietro Lió
Guido Montúfar
M. Bronstein
GNN
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Weisfeiler and Lehman Go Cellular: CW Networks"
47 / 47 papers shown
Title
Hypergraph Neural Sheaf Diffusion: A Symmetric Simplicial Set Framework for Higher-Order Learning
Seongjin Choi
Gahee Kim
Yong-Geun Oh
26
0
0
09 May 2025
SFi-Former: Sparse Flow Induced Attention for Graph Transformer
Z. Li
J. Q. Shi
X. Zhang
Miao Zhang
B. Li
44
0
0
29 Apr 2025
Higher-Order Topological Directionality and Directed Simplicial Neural Networks
M. Lecha
Andrea Cavallo
Francesca Dominici
Elvin Isufi
Claudio Battiloro
AI4CE
151
2
0
17 Jan 2025
Enhancing Graph Representation Learning with Localized Topological Features
Zuoyu Yan
Qi Zhao
Ze Ye
Tengfei Ma
Liangcai Gao
Zhi Tang
Yusu Wang
Chao Chen
47
0
0
17 Jan 2025
Degree-Conscious Spiking Graph for Cross-Domain Adaptation
Yingxu Wang
Mengzhu Wang
Siwei Liu
Shangsong Liang
Nan Yin
James Kwok
34
3
0
09 Oct 2024
TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks
Mathilde Papillon
Guillermo Bernardez
Claudio Battiloro
Nina Miolane
BDL
52
1
0
09 Oct 2024
E(n) Equivariant Topological Neural Networks
Claudio Battiloro
Ege Karaismailoglu
Mauricio Tec
George Dasoulas
Michelle Audirac
Francesca Dominici
52
5
0
24 May 2024
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers
Cai Zhou
Rose Yu
Yusu Wang
36
7
0
04 Apr 2024
Contextualized Messages Boost Graph Representations
Brian Godwin Lim
Galvin Brice Lim
Renzo Roel Tan
Kazushi Ikeda
AI4CE
70
2
0
19 Mar 2024
Topology-Informed Graph Transformer
Yuncheol Choi
Sun Woo Park
Minho Lee
Youngho Woo
28
3
0
03 Feb 2024
Uncovering Neural Scaling Laws in Molecular Representation Learning
Dingshuo Chen
Yanqiao Zhu
Jieyu Zhang
Yuanqi Du
Zhixun Li
Qiang Liu
Shu Wu
Liang Wang
32
16
0
15 Sep 2023
QDC: Quantum Diffusion Convolution Kernels on Graphs
Thomas Markovich
GNN
24
3
0
20 Jul 2023
Expectation-Complete Graph Representations with Homomorphisms
Pascal Welke
Maximilian Thiessen
Fabian Jogl
Thomas Gärtner
18
6
0
09 Jun 2023
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman
Jiarui Feng
Lecheng Kong
Hao Liu
Dacheng Tao
Fuhai Li
Muhan Zhang
Yixin Chen
44
10
0
05 Jun 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou
Xiyuan Wang
Muhan Zhang
28
14
0
08 May 2023
Graph Positional Encoding via Random Feature Propagation
Moshe Eliasof
Fabrizio Frasca
Beatrice Bevilacqua
Eran Treister
Gal Chechik
Haggai Maron
22
18
0
06 Mar 2023
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration
Xiangyu Zhao
Hannes Stärk
Dominique Beaini
Yiren Zhao
Pietro Lio'
24
0
0
27 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs
Xiaoxin He
Bryan Hooi
T. Laurent
Adam Perold
Yann LeCun
Xavier Bresson
39
88
0
27 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin
Tom Verbin
Nadav Cohen
23
10
0
29 Nov 2022
Beyond 1-WL with Local Ego-Network Encodings
Nurudin Alvarez-Gonzalez
Andreas Kaltenbrunner
Vicencc Gómez
33
5
0
27 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I
2
^2
2
-GNNs
Yinan Huang
Xingang Peng
Jianzhu Ma
Muhan Zhang
84
47
0
22 Oct 2022
Pooling Strategies for Simplicial Convolutional Networks
Domenico Mattia Cinque
Claudio Battiloro
P. Lorenzo
30
5
0
11 Oct 2022
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs
Silvia Beddar-Wiesing
Giuseppe Alessio D’Inverno
C. Graziani
Veronica Lachi
Alice Moallemy-Oureh
F. Scarselli
J. M. Thomas
31
9
0
08 Oct 2022
Expander Graph Propagation
Andreea Deac
Marc Lackenby
Petar Velivcković
96
52
0
06 Oct 2022
Multimodal learning with graphs
Yasha Ektefaie
George Dasoulas
Ayush Noori
Maha Farhat
Marinka Zitnik
51
82
0
07 Sep 2022
Agent-based Graph Neural Networks
Karolis Martinkus
Pál András Papp
Benedikt Schesch
Roger Wattenhofer
LLMAG
GNN
29
17
0
22 Jun 2022
Long Range Graph Benchmark
Vijay Prakash Dwivedi
Ladislav Rampášek
Mikhail Galkin
Alipanah Parviz
Guy Wolf
A. Luu
Dominique Beaini
26
195
0
16 Jun 2022
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks
Hao Chen
Yu Wang
Huan Xiong
GNN
14
6
0
01 Jun 2022
Recipe for a General, Powerful, Scalable Graph Transformer
Ladislav Rampášek
Mikhail Galkin
Vijay Prakash Dwivedi
A. Luu
Guy Wolf
Dominique Beaini
57
514
0
25 May 2022
Theory of Graph Neural Networks: Representation and Learning
Stefanie Jegelka
GNN
AI4CE
33
68
0
16 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
Christopher Morris
Gaurav Rattan
Sandra Kiefer
Siamak Ravanbakhsh
47
40
0
25 Mar 2022
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim
Joshua Robinson
Lingxiao Zhao
Tess E. Smidt
S. Sra
Haggai Maron
Stefanie Jegelka
49
141
0
25 Feb 2022
Structure-Aware Transformer for Graph Representation Learning
Dexiong Chen
Leslie O’Bray
Karsten M. Borgwardt
28
236
0
07 Feb 2022
A Theoretical Comparison of Graph Neural Network Extensions
Pál András Papp
Roger Wattenhofer
97
45
0
30 Jan 2022
Simplicial Convolutional Filters
Maosheng Yang
Elvin Isufi
Michael T. Schaub
G. Leus
30
32
0
27 Jan 2022
Dist2Cycle: A Simplicial Neural Network for Homology Localization
A. Keros
Vidit Nanda
Kartic Subr
19
28
0
28 Oct 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
Lingxiao Zhao
Wei Jin
L. Akoglu
Neil Shah
GNN
24
160
0
07 Oct 2021
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua
Fabrizio Frasca
Derek Lim
Balasubramaniam Srinivasan
Chen Cai
G. Balamurugan
M. Bronstein
Haggai Maron
48
175
0
06 Oct 2021
Graph Neural Networks for Graph Drawing
Matteo Tiezzi
Gabriele Ciravegna
Marco Gori
23
20
0
21 Sep 2021
Decimated Framelet System on Graphs and Fast G-Framelet Transforms
Xuebin Zheng
Bingxin Zhou
Yu Guang Wang
Xiaosheng Zhuang
40
35
0
12 Dec 2020
A Survey on The Expressive Power of Graph Neural Networks
Ryoma Sato
184
172
0
09 Mar 2020
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
189
916
0
02 Mar 2020
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
267
1,945
0
09 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
203
885
0
07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
224
1,338
0
12 Feb 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
251
1,811
0
25 Nov 2016
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
250
3,236
0
24 Nov 2016
1