Iterative deep graph learning for graph neural networks: Better and robust node embeddings

Y Chen, L Wu, M Zaki - Advances in neural information …, 2020 - proceedings.neurips.cc
In this paper, we propose an end-to-end graph learning framework, namely\textbf {I}
terative\textbf {D} eep\textbf {G} raph\textbf {L} earning (\alg), for jointly and iteratively …
被引用次数：454 相关文章
[PDF] researchgate.net

[PDF][PDF] Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, MJ Zaki - researchgate.net
In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep
Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph …

Iterative deep graph learning for graph neural networks: better and robust node embeddings

Y Chen, L Wu, MJ Zaki - … of the 34th International Conference on Neural …, 2020 - dl.acm.org
In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep
Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph …

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, M Zaki - Annual Conference on Neural …, 2020 - research.ibm.com
In this paper, we propose an end-to-end graph learning framework, namely\textbf {I}
terative\textbf {D} eep\textbf {G} raph\textbf {L} earning (\alg), for jointly and iteratively …
[PDF] rpi.edu

[PDF][PDF] Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, MJ Zaki - cs.rpi.edu
In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep
Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph …
[PDF] hugochan.net

[PDF][PDF] Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, MJ Zaki - academic.hugochan.net
In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep
Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph …

ITERATIVE DEEP GRAPH LEARNING FOR GRAPH NEURAL NETWORKS: BETTER AND ROBUST NODE EMBEDDINGS

Z Zhang - 2022 - zepengzhang.com
p= 1 sp ij, sp ij= cos (w⊙ vi, w⊙ vj), where w is a learnable weight vector. Then, to generate
a sparse non-negative adjacency matrix A from S, those elements in S which are smaller …

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, MJ Zaki - arXiv preprint arXiv:2006.13009, 2020 - arxiv.org
In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep
Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph …

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, MJ Zaki - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep
Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph …

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Y Chen, L Wu, M Zaki - Advances in Neural Information …, 2020 - proceedings.neurips.cc
In this paper, we propose an end-to-end graph learning framework, namely\textbf {I}
terative\textbf {D} eep\textbf {G} raph\textbf {L} earning (\alg), for jointly and iteratively …