Guohao Li
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Matthias Müller
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Training Graph Neural Networks with 1000 layers
DeepGCNs: Making GCNs Go as Deep as CNNs
SGAS: Sequential Greedy Architecture Search
DeepGCNs: Can GCNs Go as Deep as CNNs?
OIL: Observational Imitation Learning
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