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CS224W Papers

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Network Embedding as Matrix Factorization

Geometric Deep Learning: the Erlangen Programme of ML

Semi-Supervised Classification with Graph Convolutional Networks

Design Space of Graph Neural Networks

Inductive Representation Learning on Large Graphs

Graph Attention Networks

Hierarchical Graph Representation Learning with Differentiable Pooling

How Powerful Are Graph Neural Networks?

Identity-aware Graph Neural Networks

Graph Neural Networks are More Powerful than We Think

Counting Graph Substructures with Graph Neural Networks

Position-aware Graph Neural Networks

Do Transformers Really Perform Bad for Graph Representation?

Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Attending to Graph Transformers

Modeling Relational Data with Graph Convolutional Networks

Heterogeneous Graph Transformer

Translating Embeddings for Modeling Multi-relational Data

Learning Entity and Relation Embeddings for Knowledge Graph Completion

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

Complex Embeddings for Simple Link Prediction

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

Embedding Logical Queries on Knowledge Graphs

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