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Geometric deep learning on graphs and manifolds using mixture model CNNs
v1v2v3 (latest)

Geometric deep learning on graphs and manifolds using mixture model CNNs

25 November 2016
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
    GNN
ArXiv (abs)PDFHTML

Papers citing "Geometric deep learning on graphs and manifolds using mixture model CNNs"

50 / 862 papers shown
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient
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Maciej Besta
Afonso Claudino Catarino
Lukas Gianinazzi
Nils Blach
Piotr Nyczyk
H. Niewiadomski
Torsten Hoefler
446
10
0
30 Nov 2023
Improving embedding of graphs with missing data by soft manifolds
Improving embedding of graphs with missing data by soft manifolds
Andrea Marinoni
Pietro Lio
Alessandro Barp
Christian Jutten
Mark Girolami
250
0
0
29 Nov 2023
Deformation-Guided Unsupervised Non-Rigid Shape Matching
Deformation-Guided Unsupervised Non-Rigid Shape MatchingBritish Machine Vision Conference (BMVC), 2023
Aymen Merrouche
João Regateiro
Stefanie Wuhrer
Edmond Boyer
3DPC3DV
212
4
0
27 Nov 2023
Exploring Causal Learning through Graph Neural Networks: An In-depth
  Review
Exploring Causal Learning through Graph Neural Networks: An In-depth Review
Simi Job
Xiaohui Tao
Taotao Cai
Haoran Xie
Lin Li
Jianming Yong
Qing Li
CMLAI4CE
216
18
0
25 Nov 2023
Differentiable Visual Computing for Inverse Problems and Machine
  Learning
Differentiable Visual Computing for Inverse Problems and Machine LearningNature Machine Intelligence (Nat. Mach. Intell.), 2023
Andrew Spielberg
Fangcheng Zhong
Konstantinos Rematas
Krishna Murthy Jatavallabhula
Cengiz Öztireli
Tzu-Mao Li
Derek Nowrouzezahrai
208
13
0
21 Nov 2023
Unsupervised Multimodal Surface Registration with Geometric Deep
  Learning
Unsupervised Multimodal Surface Registration with Geometric Deep LearningMedical Image Analysis (MIA), 2023
Mohamed A. Suliman
Logan Z. J. Williams
Abdulah Fawaz
Emma C. Robinson
202
1
0
21 Nov 2023
Identification of vortex in unstructured mesh with graph neural networks
Identification of vortex in unstructured mesh with graph neural networks
Lianfa Wang
Yvan Fournier
J. Wald
Youssef Mesri
157
11
0
11 Nov 2023
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message
  Passing
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message PassingNeural Information Processing Systems (NeurIPS), 2023
Jung Yeon Park
Lawson L. S. Wong
Robin Walters
AI4CE
423
1
0
30 Oct 2023
A Metadata-Driven Approach to Understand Graph Neural Networks
A Metadata-Driven Approach to Understand Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2023
Tinghong Li
Qiaozhu Mei
Jiaqi Ma
AI4CE
266
8
0
30 Oct 2023
Projected Stochastic Gradient Descent with Quantum Annealed Binary
  Gradients
Projected Stochastic Gradient Descent with Quantum Annealed Binary GradientsBritish Machine Vision Conference (BMVC), 2023
Maximilian Krahn
Michele Sasdelli
Fengyi Yang
Vladislav Golyanik
Arno Solin
Tat-Jun Chin
Tolga Birdal
MQ
417
3
0
23 Oct 2023
MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time
  Series Anomaly Detection
MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time Series Anomaly DetectionInformation Fusion (Inf. Fusion), 2022
Chaoyue Ding
Shiliang Sun
Jing Zhao
AI4TS
245
210
0
17 Oct 2023
Graph learning in robotics: a survey
Graph learning in robotics: a surveyIEEE Access (IEEE Access), 2023
Francesca Pistilli
Giuseppe Averta
AI4CEGNN
200
16
0
06 Oct 2023
URLOST: Unsupervised Representation Learning without Stationarity or Topology
URLOST: Unsupervised Representation Learning without Stationarity or TopologyInternational Conference on Learning Representations (ICLR), 2023
Zeyu Yun
Juexiao Zhang
Bruno A. Olshausen
Yann LeCun
559
1
0
06 Oct 2023
Fast, Expressive SE$(n)$ Equivariant Networks through Weight-Sharing in
  Position-Orientation Space
Fast, Expressive SE(n)(n)(n) Equivariant Networks through Weight-Sharing in Position-Orientation SpaceInternational Conference on Learning Representations (ICLR), 2023
Erik J. Bekkers
Sharvaree P. Vadgama
Rob D. Hesselink
P. A. V. D. Linden
David W. Romero
379
38
0
04 Oct 2023
A Unified View on Neural Message Passing with Opinion Dynamics for
  Social Networks
A Unified View on Neural Message Passing with Opinion Dynamics for Social Networks
Outongyi Lv
Bingxin Zhou
Jing Wang
Xiang Xiao
Weishu Zhao
Lirong Zheng
266
3
0
02 Oct 2023
AtomSurf : Surface Representation for Learning on Protein Structures
AtomSurf : Surface Representation for Learning on Protein StructuresInternational Conference on Learning Representations (ICLR), 2023
Vincent Mallet
Souhaib Attaiki
Yangyang Miao
Bruno Correia
M. Ovsjanikov
443
5
0
28 Sep 2023
GNNHLS: Evaluating Graph Neural Network Inference via High-Level
  Synthesis
GNNHLS: Evaluating Graph Neural Network Inference via High-Level SynthesisICCD (ICCD), 2023
Chen Zhao
Zehao Dong
Yixin Chen
Xuan Zhang
Roger D. Chamberlain
GNN
174
3
0
27 Sep 2023
A Topological Machine Learning Pipeline for Classification
A Topological Machine Learning Pipeline for Classification
Francesco Conti
Davide Moroni
M. A. Pascali
129
15
0
26 Sep 2023
Neural Discovery of Permutation Subgroups
Neural Discovery of Permutation SubgroupsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Pavan Karjol
Rohan Kashyap
A. Prathosh
196
3
0
11 Sep 2023
A Unified Framework for Discovering Discrete Symmetries
A Unified Framework for Discovering Discrete SymmetriesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Pavan Karjol
Rohan Kashyap
Aditya Gopalan
Prathosh A.P.
225
6
0
06 Sep 2023
BLiSS: Bootstrapped Linear Shape Space
BLiSS: Bootstrapped Linear Shape SpaceInternational Conference on 3D Vision (3DV), 2023
Sanjeev Muralikrishnan
C. Huang
Duygu Ceylan
Niloy J. Mitra
243
3
0
04 Sep 2023
Geometric Deep Learning: a Temperature Based Analysis of Graph Neural
  Networks
Geometric Deep Learning: a Temperature Based Analysis of Graph Neural Networks
M. Lapenna
F. Faglioni
F. Zanchetta
R. Fioresi
AI4CE
58
2
0
01 Sep 2023
Explainable Graph Neural Architecture Search via Monte-Carlo Tree Search (Full version)
Explainable Graph Neural Architecture Search via Monte-Carlo Tree Search (Full version)
Yuya Sasaki
305
0
0
30 Aug 2023
Half-Hop: A graph upsampling approach for slowing down message passing
Half-Hop: A graph upsampling approach for slowing down message passingInternational Conference on Machine Learning (ICML), 2023
Mehdi Azabou
Venkataraman Ganesh
S. Thakoor
Chi-Heng Lin
Lakshmi Sathidevi
Ran Liu
Michal Valko
Petar Velickovic
Eva L. Dyer
258
30
0
17 Aug 2023
Language is All a Graph Needs
Language is All a Graph NeedsFindings (Findings), 2023
Ruosong Ye
Caiqi Zhang
Runhui Wang
Shuyuan Xu
Zelong Li
AI4CE
600
234
0
14 Aug 2023
Spatio-Temporal Encoding of Brain Dynamics with Surface Masked
  Autoencoders
Spatio-Temporal Encoding of Brain Dynamics with Surface Masked AutoencodersInternational Conference on Medical Imaging with Deep Learning (MIDL), 2023
Simon Dahan
Logan Z. J. Williams
Yourong Guo
Daniel Rueckert
E. C. Robinson
129
1
0
10 Aug 2023
PVG: Progressive Vision Graph for Vision Recognition
PVG: Progressive Vision Graph for Vision RecognitionACM Multimedia (ACM MM), 2023
Jiafu Wu
Jian Li
Jiangning Zhang
Boshen Zhang
M. Chi
Yabiao Wang
Chengjie Wang
ViT
319
20
0
01 Aug 2023
PatchMixer: Rethinking network design to boost generalization for 3D
  point cloud understanding
PatchMixer: Rethinking network design to boost generalization for 3D point cloud understandingImage and Vision Computing (IVC), 2023
Davide Boscaini
Fabio Poiesi
3DPC3DV
185
9
0
28 Jul 2023
Co-attention Graph Pooling for Efficient Pairwise Graph Interaction
  Learning
Co-attention Graph Pooling for Efficient Pairwise Graph Interaction LearningIEEE Access (IEEE Access), 2023
Junhyun Lee
Bumsoo Kim
Minji Jeon
Jaewoo Kang
GNN
186
2
0
28 Jul 2023
Improving Reliable Navigation under Uncertainty via Predictions Informed
  by Non-Local Information
Improving Reliable Navigation under Uncertainty via Predictions Informed by Non-Local InformationIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023
Raihan Islam Arnob
Gregory J. Stein
190
2
0
26 Jul 2023
How Curvature Enhance the Adaptation Power of Framelet GCNs
How Curvature Enhance the Adaptation Power of Framelet GCNs
Dai Shi
Yi Guo
Zhiqi Shao
Junbin Gao
149
16
0
19 Jul 2023
Pixel-wise Graph Attention Networks for Person Re-identification
Pixel-wise Graph Attention Networks for Person Re-identificationACM Multimedia (MM), 2021
Wenyu Zhang
Qing Ding
Jian Hu
Yi Ma
Mingzhe Lu
GNN
193
11
0
18 Jul 2023
Learning Adaptive Neighborhoods for Graph Neural Networks
Learning Adaptive Neighborhoods for Graph Neural NetworksIEEE International Conference on Computer Vision (ICCV), 2023
Avishkar Saha
Oscar Alejandro Mendez Maldonado
Chris Russell
Richard Bowden
GNN
227
11
0
18 Jul 2023
MeT: A Graph Transformer for Semantic Segmentation of 3D Meshes
MeT: A Graph Transformer for Semantic Segmentation of 3D MeshesComputer Vision and Image Understanding (CVIU), 2023
Giuseppe Vecchio
Luca Prezzavento
C. Pino
Francesco Rundo
S. Palazzo
C. Spampinato
155
9
0
03 Jul 2023
SUGAR: Spherical Ultrafast Graph Attention Framework for Cortical
  Surface Registration
SUGAR: Spherical Ultrafast Graph Attention Framework for Cortical Surface Registration
Jianxun Ren
Ning An
Youjia Zhang
Danyang Wang
Zhenyu Sun
...
Qingyu Hu
P. Zhang
D. Hu
Danhong Wang
Hesheng Liu
133
8
0
02 Jul 2023
SHARCS: Shared Concept Space for Explainable Multimodal Learning
SHARCS: Shared Concept Space for Explainable Multimodal Learning
Gabriele Dominici
Pietro Barbiero
Lucie Charlotte Magister
Pietro Lio
Nikola Simidjievski
174
6
0
01 Jul 2023
On Addressing the Limitations of Graph Neural Networks
On Addressing the Limitations of Graph Neural Networks
Sitao Luan
GNN
234
5
0
22 Jun 2023
Structure-Aware DropEdge Towards Deep Graph Convolutional Networks
Structure-Aware DropEdge Towards Deep Graph Convolutional NetworksIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Jiaqi Han
Wen-bing Huang
Yu Rong
Qifeng Bai
Gang Hua
Junzhou Huang
171
9
0
21 Jun 2023
Meta-Learning for Airflow Simulations with Graph Neural Networks
Meta-Learning for Airflow Simulations with Graph Neural Networks
Wenzhuo Liu
Mouadh Yagoubi
Marc Schoenauer
AI4CE
235
0
0
18 Jun 2023
Advancing Biomedicine with Graph Representation Learning: Recent
  Progress, Challenges, and Future Directions
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
Fang Li
Yi Nian
Zenan Sun
Cui Tao
LM&MAOODAI4TSAI4CE
210
8
0
18 Jun 2023
A Simple and Scalable Graph Neural Network for Large Directed Graphs
A Simple and Scalable Graph Neural Network for Large Directed Graphs
Seiji Maekawa
Yuya Sasaki
Makoto Onizuka
GNN
253
1
0
14 Jun 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks
Path Neural Networks: Expressive and Accurate Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2023
Gaspard Michel
Giannis Nikolentzos
J. Lutzeyer
Michalis Vazirgiannis
GNN
192
39
0
09 Jun 2023
Point-Voxel Absorbing Graph Representation Learning for Event Stream
  based Recognition
Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition
Bowei Jiang
Chengguo Yuan
Tianlin Li
Zhimin Bao
Lin Zhu
Yonghong Tian
Bin Luo
GNN3DPC
192
4
0
08 Jun 2023
Fine-grained Expressivity of Graph Neural Networks
Fine-grained Expressivity of Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2023
Jan Böker
Ron Levie
Ningyuan Huang
Soledad Villar
Christopher Morris
343
26
0
06 Jun 2023
CIN++: Enhancing Topological Message Passing
CIN++: Enhancing Topological Message Passing
Lorenzo Giusti
Teodora Reu
Francesco Ceccarelli
Cristian Bodnar
Pietro Lio
GNN
295
14
0
06 Jun 2023
Automating Style Analysis and Visualization With Explainable AI -- Case
  Studies on Brand Recognition
Automating Style Analysis and Visualization With Explainable AI -- Case Studies on Brand RecognitionDesign Automation Conference (DAC), 2023
Yu-hsuan Chen
Levent Burak Kara
Jonathan Cagan
230
5
0
05 Jun 2023
R-Mixup: Riemannian Mixup for Biological Networks
R-Mixup: Riemannian Mixup for Biological NetworksKnowledge Discovery and Data Mining (KDD), 2023
Xuan Kan
Zimu Li
Hejie Cui
Yue Yu
Ran Xu
Shaojun Yu
Zilong Zhang
Ying Guo
Carl Yang
264
8
0
05 Jun 2023
Joint Learning of Label and Environment Causal Independence for Graph
  Out-of-Distribution Generalization
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution GeneralizationNeural Information Processing Systems (NeurIPS), 2023
Shurui Gui
Meng Liu
Xiner Li
Youzhi Luo
Shuiwang Ji
CMLOOD
605
43
0
01 Jun 2023
Geometric Graph Filters and Neural Networks: Limit Properties and
  Discriminability Trade-offs
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offsIEEE Transactions on Signal Processing (IEEE TSP), 2023
Zhiyang Wang
Luana Ruiz
Alejandro Ribeiro
GNN
328
10
0
29 May 2023
Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
Physics-Regulated Deep Reinforcement Learning: Invariant EmbeddingsInternational Conference on Learning Representations (ICLR), 2023
H. Cao
Y. Mao
L. Sha
Marco Caccamo
PINNAI4CE
232
9
0
26 May 2023
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