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Lecture 4.1: Point, batch and mini-batch gradient descent
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Lecture 4.2: Batching and GNN sampling methods
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Lecture 4.3: Recap on GNN sampling methods
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Lecture 4.4: GNN batch normalization layer
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Lecture 4.5: Generalized GNN layer and Dropout
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Lecture 4.6: GNN inductive vs transductive learning
DGL_Lecture_4
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