HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers

HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers

Scalable Parallel Computing Lab, SPCL @ ETH Zurich via YouTube Direct link

Evaluation

9 of 9

9 of 9

Evaluation

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Classroom Contents

HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers

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  1. 1 Introduction: Link Prediction
  2. 2 Introduction: Higher-Order Graph Structures
  3. 3 Higher-Order Enhanced Pipeline
  4. 4 Temporal Higher-Order Structures
  5. 5 Formal Setting of Dynamic Link Prediction
  6. 6 Model Architecture: Encoding Higher-Order Structures
  7. 7 Model Architecture: Patching, Alignment and Concatenation
  8. 8 Model Architecture: Block Recurrent Transformer
  9. 9 Evaluation

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