Awesome-DynamicGraphLearning

Awesome papers (codes) about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs) and their applications (i.e. Recommender Systems).

Survey

• Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities (ARXIV, 2023) [paper]
• Graph Neural Networks Designed for Different Graph Types: A Survey (ARXIV, 2022) [paper]
• Representation Learning for Dynamic Graphs: A Survey (JMLR, 2020) [paper]
• A Survey on Embedding Dynamic Graphs (ARXIV, 2021) [paper]
• Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey (ARXIV, 2019) [paper]
• Nonlinearity + Networks: A 2020 Vision (ARXIV, 2019) [paper]
• Temporal networks (Physics Report, 2012) [paper]

Papers

2024

• TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning (IPDPS, 2024) [paper][code]
• Mayfly: a Neural Data Structure for Graph Stream Summarization (ICLR, 2024, Spotlight) [paper]
• Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks (ICLR, 2024, Poster) [paper][code]
• FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction (ICLR, 2024, Poster) [paper][code]
• PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks (ICLR, 2024, Poster) [paper][code]
• Hypergraph Dynamic System (ICLR, 2024, Poster) [paper]
• Deep Temporal Graph Clustering (ICLR, 2024, Poster) [paper][code]
• GraphPulse: Topological representations for temporal graph property prediction (ICLR, 2024, Poster) [paper][code]
• Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs (ICLR, 2024, Poster) [paper][code]
• Temporal Generalization Estimation in Evolving Graphs (ICLR, 2024, Poster) [paper]
• Dynamic Graph Information Bottleneck (**https://arxiv.org/pdf/2402.06716.pdforg/pdf/2402.06716.pdf)][code]
• On the Feasibility of Simple Transformer for Dynamic Graph Modeling (**https://arxiv.org/pdf/2401.14009.pdforg/pdf/2401.14009.pdf)]
• Temporal Conformity-aware Hawkes Graph Network for Recommendations (WWW, 2024)
• IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion (WWW, 2024)
• TATKC: A Temporal Graph Neural Network for Fast Approximate Temporal Katz Centrality Ranking (WWW, 2024)
• Efficient exact and approximate betweenness centrality computation for temporal graphs (WWW, 2024)

2023

• DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training (SC, 2023) [paper][code]
• Towards Better Dynamic Graph Learning: New Architecture and Unified Library (ARXIV, 2023) [paper][code]
• SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning (ARXIV, 2023) [paper][code]
• Towards Open Temporal Graph Neural Networks (ICLR, 2023) [paper][code]
• Do We Really Need Complicated Model Architectures For Temporal Networks? (ICLR, 2023) [paper][code]
• Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank (VLDB, 2023) [paper][code]
• Temporal SIR-GN: Eficient and Efective Structural Representation Learning for Temporal Graphs (VLDB, 2023) [paper][code]
• SEIGN: A Simple and Efficient Graph Neural Network for Large Dynamic Graphs (ICDE, 2023) [paper]
• A Higher-Order Temporal H-Index for Evolving Networks (KDD, 2023) [paper]
• Using Motif Transitions for Temporal Graph Generation (KDD, 2023) [paper]
• Temporal Dynamics Aware Adversarial Attacks on Discrete-Time Graph Models (KDD, 2023) [paper][code]
• Fairness-Aware Continuous Predictions of Multiple Analytics Targets in Dynamic Networks (KDD, 2023) [paper]
• DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph (KDD, 2023) [paper]
• WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window (KDD, 2023)
• Community-based Dynamic Graph Learning for Popularity Prediction (KDD, 2023)
• An Atentional Multi-scale Co-evolving Model for Dynamic Link Prediction (**https://dl.acm.org/doi/pdf/10.1145/3543507.35833960.1145/3543507.3583396)][code]
• TIGER: Temporal Interaction Graph Embedding with Restarts (**https://arxiv.org/pdf/2302.06057.pdforg/pdf/2302.06057.pdf)][code]
• HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction (**https://arxiv.org/pdf/2304.07302.pdforg/pdf/2304.07302.pdf)][code]
• Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs (**https://dl.acm.org/doi/pdf/10.1145/3543507.35834760.1145/3543507.3583476)][code]
• Local Edge Dynamics and Opinion Polarization (WSDM, 2023) [paper][code]
• Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs (WSDM, 2023) [paper][code]
• Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs (WSDM, 2023) [paper]
• Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks (AAAI, 2023) [paper][code]

2022

• TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs (VLDB, 2022) [paper][code]
• Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs (Neurips, 2022)[paper][code]
• Adaptive Data Augmentation on Temporal Graphs (Neurips, 2022) [paper]
• Parameter-free Dynamic Graph Embedding for Link Prediction (Neurips, 2022) [paper][code]
• Instant Graph Neural Networks for Dynamic Graphs (KDD, 2022) [paper][code]
• Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction (KDD, 2022) [paper][code]
• ROLAND: Graph Learning Framework for Dynamic Graphs (KDD, 2022) [paper][code]
• Subset Node Anomaly Tracking over Large Dynamic Graphs (KDD, 2022) [paper][code]
• Streaming Graph Neural Networks via Generative Replay (KDD, 2022) [paper][code]
• Neighborhood-aware Scalable Temporal Network Representation Learning (LoG, 2022) [paper][code]
• DisenCTR: Dynamic Graph-based Disentangled Representation for Click-Through Rate Prediction (SIGIR, 2022) [paper][code]
• STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation (**https://keg.cs.tsinghua.edu.cn/jietang/publications/WWW22-Yang%20et%20al.-STAM-GNN.pdf0et%20al.-STAM-GNN.pdf)][code]
• Neural Predicting Higher-order Patterns in Temporal Networks (**https://arxiv.org/pdf/2106.06039.pdforg/pdf/2106.06039.pdf)][code]
• TREND: TempoRal Event and Node Dynamics for Graph Representation Learning (**https://arxiv.org/pdf/2203.14303.pdforg/pdf/2203.14303.pdf)][code]
• A Viral Marketing-Based Model For Opinion Dynamics in Online Social Networks (**https://arxiv.org/pdf/2202.03573.pdforg/pdf/2202.03573.pdf)]
• EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs (WSDM, 2022) [paper][code]
• Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs (WSDM, 2022) [paper][code]
• Few-shot Link Prediction in Dynamic Networks (WSDM, 2022) [paper]
• On Generalizing Static Node Embedding to Dynamic Settings (WSDM, 2022) [paper]
• Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion (CIKM, 2022) [paper][code]
• DA-Net: Distributed Attention Network for Temporal Knowledge Graph Reasoning (CIKM, 2022) [paper]
• A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning (CIKM, 2022) [paper]
• Dynamic Hypergraph Learning for Collaborative Filtering (CIKM, 2022) [paper]

2021

• Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks (ICLR, 2021) [paper][code]
• Coupled Graph ODE for Learning Interacting System Dynamics (KDD, 2021) [paper][code]
• Subset Node Representation Learning over Large Dynamic Graphs (KDD, 2021) [paper][code]
• Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space [paper][code]
• Learning to Walk across Time for Temporal Knowledge Graph Completion (KDD, 2021) [paper]
• Forecasting Interaction Order on Temporal Graphs (KDD, 2021)
• Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning (SIGIR, 2021) [paper][code]
• Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences (SIGIR, 2021)
• TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion [paper]
• SDG: A Simplified and Dynamic Graph Neural Network (SIGIR SHORT, 2021) [paper][code]
• Temporal Augmented Graph Neural Networks for Session-Based Recommendations (SIGIR SHORT, 2021) [paper]
• HINTS: Citation Time Series Prediction for New Publications via Dynamic Heterogeneous Information Network Embedding (**http://web.cs.ucla.edu/~yzsun/papers/2021_WWW_HINTS.pdfers/2021_https://github.com/songjiang0909/HINTS_codeongjiang0909/HINTS_code)]
• TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks (**http://snap.stanford.edu/tedic/files/www21_tedic.pdf/files/www21_tedic.pdf)]
• Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs (AAAI, 2021) [paper]
• Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks (AAAI, 2021) [paper][code]
• Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay (AAAI, 2021) [paper]
• Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network (WSDM, 2021) [paper]
• F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams (WSDM, 2021) [paper][code]
• Cache-based GNN System for Dynamic Graphs (CIKM 2021) [[paper]]
• Self-supervised Representation Learning on Dynamic Graphs (CIKM 2021)[[paper]]
• Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer [paper][code]
• Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs (CIKM 2021) [paper]
• Neural Higher-order Pattern (Motif) Prediction in Temporal Networks (ARXIV, 2021) [paper]

2020

• Inductive Representation Learning on Temporal Graphs (ICLR, 2020) [paper][code]
• Temporal Graph Networks for Deep Learning on Dynamic Graphs (ICML Workshop, 2020) [paper][code]
• A Data-Driven Graph Generative Model for Temporal Interaction Networks (KDD, 2020) [paper][code]
• Dynamic Knowledge Graph based Multi-Event Forecasting (KDD, 2020) [paper][code]
• Laplacian Change Point Detection for Dynamic Graphs (KDD, 2020) [paper][code]
• Algorithmic Aspects of Temporal Betweenness (KDD, 2020) [paper][code]
• Heterogeneous Graph Transformer (**https://arxiv.org/pdf/2003.01332.pdforg/pdf/2003.01332.pdf)][code]
• Streaming Graph Neural Network (SIGIR, 2020) [paper][code]
• Next-item Recommendation with Sequential Hypergraphs (SIGIR, 2020) [paper][code]
• Temporal Network Embedding with High-Order Nonlinear Information (AAAI, 2020) [paper]
• Motif-Preserving Temporal Network Embedding (IJCAI, 2020) [paper]
• Dynamic Graph Collaborative Filtering (ICDM, 2020) [paper][code]
• DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks (WSDM, 2020) [papr][code]
• Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network (WSDM, 2020) [paper][code]
• Continuous-Time Dynamic Graph Learning via Neural Interaction Processes (CIKM, 2020) [paper]
• tdGraphEmbed: Temporal Dynamic Graph-Level Embedding (CIKM, 2020) [paper][code]
• Streaming Graph Neural Network via Continue Learning (CIKM, 2020) [paper][code]
• Disentangle-based Continual Graph Representation Learning (EMNLP, 2020) [paper][code]
• TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion (EMNLP, 2020) [paper][code]
• Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs (EMNLP, 2020) [paper][code]
• EPNE: Evolutionary Pattern Preserving Network Embedding (ECAI, 2020) [paper]
• GloDyNE: Global Topology Preserving Dynamic Network Embedding (TKDE, 2020) [paper][code]
• Dynamic Heterogeneous Information Network Embedding with Meta-path based Proximity (TKDE, 2020) [paper][code]
• Lifelong Graph Learning (ARXIV, 2020) [paper]

2019

• Variational Graph Recurrent Neural Networks (NeurIPS, 2019) [paper][code]
• Recurrent Space-time Graph Neural Networks (NeurIPS, 2019) [paper][code]
• DyRep: Learning Representations over Dynamic Graphs (ICLR, 2019) [paper]
• Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks (KDD, 2019) [paper][code]
• Learning Dynamic Context Graphs for Predicting Social Events (KDD, 2019) [paper][code]
• EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs (AAAI, 2019) [paper][code]
• Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems (**https://arxiv.org/pdf/1904.04381.pdforg/pdf/1904.04381.pdf)]
• Real-Time Streaming Graph Embedding Through Local Actions (**https://nickduffield.net/download/papers/DL4G-SDE-2019.pdfpers/DL4G-SDE-2019.pdf)]
• Dynamic Hypergraph Neural Networks (IJCAI, 2019) [paper][code]
• Node Embedding over Temporal Graphs (IJCAI, 2019) [paper][code]
• Temporal Network Embedding with Micro- and Macro-dynamics (CIKM, 2019) [paper][code]

2018

• NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks (KDD, 2018) [paper][code]
• Embedding Temporal Network via Neighborhood Formation (KDD, 2018) [paper][code]
• Dynamic Network Embedding by Modeling Triadic Closure Process (AAAI, 2018) [paper][code]
• Continuous-Time Dynamic Network Embeddings (**https://dl.acm.org/doi/pdf/10.1145/3184558.31915260.1145/3184558.3191526)][code]
• Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding (IJCAI, 2018) [paper]

2017

• Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs (ICML, 2017) [paper][code]
• The Co-Evolution Model for Social Network Evolving and Opinion Migration (KDD, 2017) [papercode]
• Attributed Network Embedding for Learning in a Dynamic Environment (CIKM, 2017) [paper][code]

Tools

General Graph Learning

• Deep Graph Library
• Pytorch Geometric
• Pytorch Geometric Temporal
• Stellar Graph
• GraphVite

Knowledge Graph

• DGL-KE
• OpenKE

Recommender System

• RecBole