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Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs
Neural Information Processing Systems (NeurIPS), 2022
9 February 2022
Cristian Bodnar
Francesco Di Giovanni
B. Chamberlain
Pietro Lio
Michael M. Bronstein
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Papers citing
"Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs"
36 / 136 papers shown
DRew: Dynamically Rewired Message Passing with Delay
International Conference on Machine Learning (ICML), 2023
Benjamin Gutteridge
Xiaowen Dong
Michael M. Bronstein
Francesco Di Giovanni
299
87
0
13 May 2023
Deep Learning and Geometric Deep Learning: an introduction for mathematicians and physicists
International Journal of Geometric Methods in Modern Physics (IJGMMP) (IJGMMP), 2023
R. Fioresi
F. Zanchetta
PINN
123
6
0
09 May 2023
Zoo Guide to Network Embedding
Anthony Baptista
Rubén J. Sánchez-García
A. Baudot
Ginestra Bianconi
GNN
207
11
0
05 May 2023
GCNH: A Simple Method For Representation Learning On Heterophilous Graphs
IEEE International Joint Conference on Neural Network (IJCNN), 2023
Andrea Cavallo
Claas Grohnfeldt
Michele Russo
Giulio Lovisotto
L. Vassio
159
14
0
21 Apr 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks
Neural Information Processing Systems (NeurIPS), 2023
Weitao Du
Yuanqi Du
Limei Wang
Dieqiao Feng
Guifeng Wang
Shuiwang Ji
Daniel Schwalbe-Koda
Zhixin Ma
AI4CE
261
54
0
07 Apr 2023
Sheaf4Rec: Sheaf Neural Networks for Graph-based Recommender Systems
ACM Transactions on Recommender Systems (ACM TORS), 2023
Antonio Purificato
Giulia Cassara
F. Siciliano
Pietro Lio
Fabrizio Silvestri
207
9
0
07 Apr 2023
Interpretable statistical representations of neural population dynamics and geometry
Nature Methods (Nat Methods), 2023
Adam Gosztolai
Robert L. Peach
Alexis Arnaudon
Mauricio Barahona
P. Vandergheynst
314
25
0
06 Apr 2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back
IEEE Transactions on Signal Processing (IEEE TSP), 2023
Claudio Battiloro
Zhiyang Wang
Hans Riess
Paolo Di Lorenzo
Alejandro Ribeiro
224
16
0
20 Mar 2023
A Survey on Oversmoothing in Graph Neural Networks
T. Konstantin Rusch
Michael M. Bronstein
Siddhartha Mishra
242
308
0
20 Mar 2023
Graph Neural Networks in Vision-Language Image Understanding: A Survey
The Visual Computer (TVC), 2023
Henry Senior
Greg Slabaugh
Shanxin Yuan
Luca Rossi
GNN
323
34
0
07 Mar 2023
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?
International Conference on Learning Representations (ICLR), 2023
Oleg Platonov
Denis Kuznedelev
Michael Diskin
Artem Babenko
Liudmila Prokhorenkova
294
318
0
22 Feb 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
International Conference on Machine Learning (ICML), 2023
Francesco Di Giovanni
Lorenzo Giusti
Federico Barbero
Giulia Luise
Pietro Lio
Michael M. Bronstein
404
174
0
06 Feb 2023
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
Antonio Longa
Veronica Lachi
G. Santin
Monica Bianchini
Bruno Lepri
Pietro Lio
F. Scarselli
Baptiste Caramiaux
AI4CE
567
91
0
02 Feb 2023
State of the Art and Potentialities of Graph-level Learning
ACM Computing Surveys (ACM Comput. Surv.), 2023
Zhenyu Yang
Ge Zhang
Hongzhi Zhang
Jian Yang
Quan.Z Sheng
...
Charu C. Aggarwal
Hao Peng
Wenbin Hu
Edwin R. Hancock
Pietro Lio
GNN
AI4CE
279
26
0
14 Jan 2023
2-hop Neighbor Class Similarity (2NCS): A graph structural metric indicative of graph neural network performance
Andrea Cavallo
Claas Grohnfeldt
Michele Russo
Giulio Lovisotto
L. Vassio
GNN
153
17
0
26 Dec 2022
Multi-duplicated Characterization of Graph Structures using Information Gain Ratio for Graph Neural Networks
IEEE Access (IEEE Access), 2022
Yuga Oishi
Ken Kaneiwa
231
1
0
24 Dec 2022
Latent Graph Inference using Product Manifolds
International Conference on Learning Representations (ICLR), 2022
Haitz Sáez de Ocáriz Borde
Anees Kazi
Federico Barbero
Pietro Lio
BDL
313
22
0
26 Nov 2022
GREAD: Graph Neural Reaction-Diffusion Networks
International Conference on Machine Learning (ICML), 2022
Jeongwhan Choi
Seoyoung Hong
Noseong Park
Sung-Bae Cho
DiffM
GNN
266
56
0
25 Nov 2022
Improving Graph Neural Networks with Learnable Propagation Operators
International Conference on Machine Learning (ICML), 2022
Moshe Eliasof
Lars Ruthotto
Eran Treister
250
28
0
31 Oct 2022
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Claudio Battiloro
Zhiyang Wang
Hans Riess
P. Lorenzo
Alejandro Ribeiro
283
15
0
26 Oct 2022
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks
Neural Information Processing Systems (NeurIPS), 2022
Chenxiao Yang
Qitian Wu
Junchi Yan
233
27
0
24 Oct 2022
Revisiting Heterophily For Graph Neural Networks
Neural Information Processing Systems (NeurIPS), 2022
Sitao Luan
Chenqing Hua
Qincheng Lu
Jiaqi Zhu
Mingde Zhao
Shuyuan Zhang
Xiaoming Chang
Doina Precup
228
264
0
14 Oct 2022
Generalized energy and gradient flow via graph framelets
Andi Han
Dai Shi
Zhiqi Shao
Junbin Gao
288
16
0
08 Oct 2022
Cell Attention Networks
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Lorenzo Giusti
Claudio Battiloro
Lucia Testa
P. Lorenzo
S. Sardellitti
Sergio Barbarossa
3DPC
GNN
847
40
0
16 Sep 2022
Graph Convolutional Networks from the Perspective of Sheaves and the Neural Tangent Kernel
Thomas Gebhart
GNN
107
1
0
19 Aug 2022
Ordered Subgraph Aggregation Networks
Neural Information Processing Systems (NeurIPS), 2022
Chao Qian
Gaurav Rattan
Floris Geerts
Christopher Morris
Mathias Niepert
346
70
0
22 Jun 2022
Understanding convolution on graphs via energies
Francesco Di Giovanni
J. Rowbottom
B. Chamberlain
Thomas Markovich
Michael M. Bronstein
GNN
289
67
0
22 Jun 2022
Sheaf Neural Networks with Connection Laplacians
Federico Barbero
Cristian Bodnar
Haitz Sáez de Ocáriz Borde
Michael M. Bronstein
Petar Velivcković
Pietro Lio
188
51
0
17 Jun 2022
Not too little, not too much: a theoretical analysis of graph (over)smoothing
Neural Information Processing Systems (NeurIPS), 2022
Nicolas Keriven
376
142
0
24 May 2022
Graph Anisotropic Diffusion
Ahmed A. A. Elhag
Gabriele Corso
Hannes Stärk
Michael M. Bronstein
DiffM
GNN
175
0
0
30 Apr 2022
Graph Attention Retrospective
Journal of machine learning research (JMLR), 2022
Kimon Fountoulakis
Amit Levi
Shenghao Yang
Aseem Baranwal
Aukosh Jagannath
GNN
529
42
0
26 Feb 2022
Graph Neural Networks for Graphs with Heterophily: A Survey
Xin-Yang Zheng
Yi Wang
Yixin Liu
Ming Li
Miao Zhang
Di Jin
Philip S. Yu
Shirui Pan
333
283
0
14 Feb 2022
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem
Knowledge Discovery and Data Mining (KDD), 2022
Guanyu Cui
Zhewei Wei
173
12
0
31 Jan 2022
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
Moshe Eliasof
Ben Bodner
Eran Treister
GNN
241
11
0
10 Oct 2021
Adaptive Universal Generalized PageRank Graph Neural Network
International Conference on Learning Representations (ICLR), 2020
Eli Chien
Jianhao Peng
Pan Li
O. Milenkovic
995
925
0
14 Jun 2020
Benchmarking Graph Neural Networks
Journal of machine learning research (JMLR), 2023
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
1.4K
1,110
0
02 Mar 2020
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