Graph-Learning-Chinese-

在此整理了一些个人感兴趣的文献阅读，主要是与heterophilic & Temporal Graph学习领域相关的，希望大家多多指正。

Survey

• Graph Neural Networks for Graphs with Heterophily: A Survey (Arxiv) [paper]

• Graph self-supervised learning: A survey (TKDE 2022) [paper]

• A Survey on Network Embedding (AAAI 2017) [paper]

Homo&Heter Paper

2024

• Revisiting the Role of Heterophily in Graph Representation Learning: An Edge Classification Perspective (TKDD) [paper]

2023

• HomoGCL: Rethinking Homophily in Graph Contrastive Learning (KDD) [paper][code]

• Spatial Heterophily Aware Graph Neural Networks (KDD) [paper]

• Attribute and Structure Preserving Graph Contrastive Learning (AAAI) [paper]code]

• Generalized heterophily graph data augmentation for node classification (Neural Networks) [paper]

2022

• Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily (AAAI) [paper]code]

• Finding Global Homophily in Graph Neural Networks When Meeting Heterophily (ICML) [paper]code]

• Is Homophily a Necessity for Graph Neural Networks? (ICLR) [paper]

• Automated Self-Supervised Learning for Graphs (ICLR) [paper)]code]

• Revisiting Heterophily For Graph Neural Networks (NeurIPS) [paper)]code]

2021

• Adaptive Universal Generalized PageRank Graph Neural Network (ICLR) [paper)]code]

• Node Similarity Preserving Graph Convolutional Networks (WSDM) [paper)]code]

2020

• Towards Deeper Graph Neural Networks (KDD) [paper)]code]

• Geom-GCN: Geometric Graph Convolutional Networks (ICLR) [paper)]re_code]

• Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs (NeurIPS) [paper)]code]

Temporal Graph

2021

• Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer (CIKM) [paper][code]

• Do Transformers Really Perform Bad for Graph Representation (NeurIPS) [paper][code]

• Structural Deep Clustering Network (WWW) [paper][code]

• Deep Fusion Clustering Network (AAAI) [paper][code]

• Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks (ICLR) [paper][code]

• Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay (AAAI) [paper]

• Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (ICLR) [paper][code]

• Accurate Learning of Graph Representations with Graph Multiset Pooling (ICLR) [paper][code]

• Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting (AAAI Best Paper) [paper][code]

• Self-supervised Graph Learning for Recommendation (SIGIR) [paper][code]

• Learnable Embedding Sizes for Recommender Systems (ICLR) [paper][code]

• Adversarial Directed Graph Embedding (AAAI) [paper][code]

• Graph Game Embedding (AAAI) [paper]

• Towards Robust Graph Contrastive Learning (WWW Workshop) [paper]

• Towards open-world feature extrapolation: An inductive graph learning approach (NeurIPS) [paper]

• Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis (ACL) [paper][code]

• How to Find Your Friendly Neighborhood: Graph Attention Design with Self-supervision (ICLR) [paper][code]

2020

• Contrastive Multi-View Representation Learning on Graphs (ICML) [paper][code]

• Temporal Graph Networks for Deep Learning on Dynamic Graphs (ICML Workshop) [paper][code]

• Inductive representation learning on temporal graphs (ICLR) [paper][code]

• EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graph (AAAI) [paper][code]

• DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks (WSDM) [paper][code]

• Inductive and Unsupervised Representation Learning on Graph Structured Objects (ICLR) [paper]

• GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training (KDD) [paper][code]

• JNET: Learning User Representations via Joint Network Embedding and Topic Embedding (WSDM) [paper][code]

• Deep Graph Contrastive Representation Learning (ICML Workshop) [paper][code]

• On the equivalence between positional node embeddings and structural graph representations (ICLR) [paper]

• Explain Graph Neural Networks to Understand Weight Graph Features (IFIP) [paper]

2019

• DyREP: Learing Representations over Dynamic Graphs (ICLR) [paper]

• Self-attention with Functional Time Representation Learning (NeurIPS) [paper][code]

• Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks (KDD) [paper][code][slide][note]

• Node Embedding over Temporal Graphs (IJCAI) [paper][code]

• Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graph (IJCAI) [paper][code]

• GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding (WWW) [paper][code]

2018

• Continuous-Time Dynamic Network Embeddings (WWW) [paper][code][note]

• Embedding Temporal Network via Neighborhood Formation (KDD) [paper]

• Learning dynamic embeddings from temporal interactions (arXiv) [paper]

• Arbitrary-Order Proximity Preserved Network Embedding (KDD) [paper][code]

• A Unified Framework for Community Detection and Network Representation Learning (TKDE) [paper]

2017

• CANE: Context-Aware Network Embedding for Relation Modeling (ACL) [paper][code][slide]

• Inductive representation learning on large graph (NeurIPS) [paper][code]

• PRISM: Profession Identification in Social Media (ACM) [paper]

• TransNet: Translation-Based NRL for Social Relation Extraction (IJCAI) [paper][code]

• Learning Community Embedding with Community Detection and Node Embedding on Graphs (CIKM) [paper][code]

2016

• Asymmetric Transitivity Preserving Graph Embedding (KDD) [paper][code]

• Structural Deep Network Embedding (KDD) [paper][code]

• node2vec: Scalable Feature Learning for Networks (KDD) [paper][code]

• Max-Margin DeepWalk: Discriminative Learning of Network Representation (IJCAI) [paper][code]

2015

• LINE: Large-scale Information Network Embedding (WWW) [paper][code]

2014

• DeepWalk: online learning of social representations (KDD) [paper][code]