Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks (original) (raw)
Related papers
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters
2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Node-Variant Graph Filters in Graph Neural Networks
2022 IEEE Data Science and Learning Workshop (DSLW)
Adaptive Filters in Graph Convolutional Neural Networks
Cornell University - arXiv, 2021
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks
IEEE Signal Processing Magazine, 2020
Pointspectrum: Equivariance Meets Laplacian Filtering for Graph Representation Learning
2021
Graph Neural Networks with Convolutional ARMA Filters
Graph Neural Networks with Convolutional ARMA Filters, 2019
Stability and Generalization of Graph Convolutional Neural Networks
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks
ArXiv, 2020
Graph Neural Networks Are More Powerful Than we Think
arXiv (Cornell University), 2022
Dynamic Filters in Graph Convolutional Neural Networks
ArXiv, 2021
Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs
2019 27th European Signal Processing Conference (EUSIPCO), 2019
Robust Graph Neural Networks using Weighted Graph Laplacian
arXiv (Cornell University), 2022
arXiv (Cornell University), 2021
Discrete and Continuous Deep Residual Learning over Graphs
2021
A Higher-Order Graph Convolutional Layer
2018
What Do Graph Convolutional Neural Networks Learn?
2022
A Network Science perspective of Graph Convolutional Networks: A survey
arXiv (Cornell University), 2023
Convolutional Graph Neural Networks
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification
Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18, 2018
A Comprehensive Survey on Graph Neural Networks
IEEE Transactions on Neural Networks and Learning Systems, 2020
Large-Scale Learnable Graph Convolutional Networks
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Improving Graph Convolutional Networks with Non-Parametric Activation Functions
2018
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
ArXiv, 2020
Graph Signal Processing -- Part III: Machine Learning on Graphs, from Graph Topology to Applications
arXiv (Cornell University), 2020
Residual convolutional graph neural network with subgraph attention pooling
Tsinghua Science and Technology, 2022
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
ACM Computing Surveys
SGCN: A Graph Sparsifier Based on Graph Convolutional Networks
Advances in Knowledge Discovery and Data Mining
Introduction to Graph Neural Networks
Synthesis Lectures on Artificial Intelligence and Machine Learning, 2020
Higher-order Sparse Convolutions in Graph Neural Networks
arXiv (Cornell University), 2023
Convolutional Neural Networks via Node-Varying Graph Filters
2018 IEEE Data Science Workshop (DSW), 2018
GraphMix: Improved Training of Graph Neural Networks for Semi-Supervised Learning
2020
GFCN: A New Graph Convolutional Network Based on Parallel Flows
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Robust Mid-Pass Filtering Graph Convolutional Networks
Proceedings of the ACM Web Conference 2023
Higher-Order Sparse Convolutions In Graph Neural Network
Thierry BOUWMANS, Jhony Heriberto Giraldo Zuluaga
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, 2023