Awesome-Graph-Structure-Learning

This repository contains a curated list of papers on (or related to) graph structure learning (GSL), which are categorized based on their published years.

Keyword

The application task in each paper, e.g., general graph learning, recommendation, and anomaly detection.

Continuously updating!

---

Research Paper

Year 2023

(KDD 2023) GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks [PDF] [Code]

(WWW 2023) SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization [PDF] [Code]

Year 2022

(KDD 2022) Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN [PDF]

(WWW 2022) Towards Unsupervised Deep Graph Structure Learning [PDF] [Code]

(WWW 2022) GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction [PDF] [Code]

(AAAI 2022) Graph Structure Learning with Variational Information Bottleneck [PDF] [Code]

Year 2021

(AAAI 2021) Heterogeneous Graph Structure Learning for Graph Neural Networks [PDF] [Code]

(CIKM 2021) Speedup Robust Graph Structure Learning with Low-Rank Information [PDF]

Year 2020 & Before

(KDD 2020) Graph Structure Learning for Robust Graph Neural Networks [PDF] [Code]

(ICML 2019) DAG-GNN: DAG Structure Learning with Graph Neural Networks [PDF] [Code]

(ICDM 2018) Deep Structure Learning for Fraud Detection [PDF] [Code]

---

Survey Paper

(Arxiv 2021) A Survey on Graph Structure Learning: Progress and Opportunities [PDF]

---

Benchmark

(NIPS 2023) OpenGSL: A Comprehensive Benchmark for Graph Structure Learning [PDF] [Code]

(NIPS 2023) GSLB: The Graph Structure Learning Benchmark [PDF] [Code]