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DGL for Abstract Meaning Representation
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1
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5
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July 13, 2020
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Training with the random generated synthetic features
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3
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15
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July 13, 2020
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Multigraph depreciation
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4
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58
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July 13, 2020
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Examples of PyTorch for "Run multi-processing training" in "Large-Scale Training of Graph Neural Networks" Tutorial
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4
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102
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July 13, 2020
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Load properties from networkx graph
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3
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22
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July 12, 2020
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Load_graph error
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2
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27
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July 10, 2020
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The probability of a positive class in the binary classification
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6
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45
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July 9, 2020
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Own dataset and heterograph
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8
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45
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July 9, 2020
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Accuracy of training beyond 1.0
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3
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32
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July 9, 2020
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Error when assign node features
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11
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63
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July 8, 2020
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Suggestion for improving graph classification
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3
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43
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July 7, 2020
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Error with starting trainer for large graphs
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5
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58
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July 6, 2020
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Nodeflow example with Torch
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7
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79
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July 6, 2020
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More than one graph features
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2
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33
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July 6, 2020
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Confusion regarding DGLGraph.local_var
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4
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61
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July 6, 2020
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Pinsage example implementation different than the paper
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2
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45
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July 6, 2020
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Gradient correctness
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4
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56
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July 6, 2020
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Neighbor Sampling in Heterogeneous Graphs
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2
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65
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July 6, 2020
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Hello, when I implemented the R-GCN code, such a problem occurred
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7
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75
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July 3, 2020
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Extending DGL tutorial to use node and edge features
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4
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78
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June 30, 2020
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Tree LSTM nodes mailbox
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3
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63
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June 29, 2020
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Problems in example pytorch.graphsage.train_sampling.py
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3
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49
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June 29, 2020
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How to get the src and dst node id given a edge id?
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2
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60
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June 28, 2020
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Problems with save_graphs
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2
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43
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June 28, 2020
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Using node and edge features in message passing
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4
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210
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June 27, 2020
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GraphSAGE with edge features?
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3
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112
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June 25, 2020
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Weighted meta path
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2
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49
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June 25, 2020
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CUDA related error in multi_update_all
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2
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32
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June 25, 2020
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Convert graph from networkx format to dgl
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4
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67
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June 24, 2020
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How does DGL save gpu memory?
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2
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67
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June 24, 2020
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