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	NeurIPS 2021 \|\| DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks Paper (Higher Education Goals and Research ) View
	Improving Graph Neural Networks with Structural Adaptive Receptive Fields (VideoLecturesChannel) View
	[Deep Graph Learning] 4.4 GNN batch normalization layer (BASIRA Lab) View
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	ICPRS2021 Paper 31 (ICPRS) View
	[Deep Graph Learning] 4.1 Point, batch and mini-batch gradient descent (BASIRA Lab) View
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	GNN-Surrogate: PacificVis2022 presentation (Neng Shi) View
	Employing knowledge graphs and Graph Neural Networks (GNNs) for patent research (AI u0026 Patents 2021) (AI and Patents Workshop at ICAIL 2021) View
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