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ZHEWEI WEI
Browse, search & ask about the research work by "SAHAND NEGAHBAN"
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Selected work | Use "Search" to find all #paper(s): 137
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Paper
Simple and Deep Graph Convolutional Networks
IF:8
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: In this paper, we study the problem of designing and analyzing deep graph convolutional networks.
MING CHEN
et. al.
icml
2020-07-11
Paper
Mergeable Summaries
IF:5
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Abstract:
We study the mergeability of data summaries. Informally speaking, mergeability requires that, given two summaries on two data sets, there is a way to merge the two summaries into ...
PANKAJ K. AGARWAL
et. al.
2012-01-01
Paper
BernNet: Learning Arbitrary Graph Spectral Filters Via Bernstein Approximation
IF:4
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: To overcome these issues, we propose BernNet, a novel graph neural network with theoretical support that provides a simple but effective scheme for designing and learning arbitrary graph spectral filters.
MINGGUO HE
et. al.
arxiv-cs.LG
2021-06-21
Paper
Scalable Graph Neural Networks Via Bidirectional Propagation
IF:4
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: In this paper, we present GBP, a scalable GNN that utilizes a localized bidirectional propagation process from both the feature vector and the training/testing nodes.
MING CHEN
et. al.
nips
2020-11-17
Paper
Scalable Graph Neural Networks Via Bidirectional Propagation
IF:4
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: This paper presents GBP, a scalable GNN that utilizes a localized bidirectional propagation process from both the feature vectors and the training/testing nodes.
MING CHEN
et. al.
arxiv-cs.LG
2020-10-29
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