Awesome papers (codes) about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs) and their applications (i.e. Recommender Systems).
- Deep learning for dynamic graphs: models and benchmarks (TNNLS, 2024) [paper][code]
- 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]
- Long Range Propagation on Continuous-Time Dynamic Graphs (ICML, 2024) [paper][code]
- LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs? (SIGKDD, 2024) [paper][code]
- Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling (SIGKDD, 2024) [paper]
- SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning (SIGKDD, 2024) [paper][code]
- Predicting Long-term Dynamics of Complex Networks via Identifying Skeleton in Hyperbolic Space (SIGKDD, 2024) [code]
- Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model (SIGKDD, 2024) [paper][code]
- MemMap: An Adaptive and Latent Memory Structure for Dynamic Graph Learning (SIGKDD, 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]
- HOPE: High-order Graph ODE For Modeling Interacting Dynamics (ICML, 2024, Poster) [paper]
- Temporal Generalization Estimation in Evolving Graphs (ICLR, 2024, Poster) [paper]
- Dynamic Graph Information Bottleneck (WWW, 2024) [paper][code]
- On the Feasibility of Simple Transformer for Dynamic Graph Modeling (WWW, 2024) [paper]
- 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)
- Temporal Graph ODEs for Irregularly-Sampled Time Series (IJCAI, 2024) [paper][code]
- Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning (Neurips 2024 Submission) [paper][code]
- Anomaly Detection in Continuous-Time Temporal Provenance Graphs (Temporal Graph Learning Workshop @ NeurIPS, 2023) [paper][code]
- Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts (Neurips, 2023) [paper][code]
- 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 (WWW, 2023) [paper][code]
- TIGER: Temporal Interaction Graph Embedding with Restarts (WWW, 2023) [paper][code]
- HGWaveNet: A Hyperbolic Graph Neural Network for Temporal Link Prediction (WWW, 2023) [paper][code]
- Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs (WWW, 2023) [paper][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]
- Dynamic Heterogeneous Graph Attention Neural Architecture Search (AAAI, 2023) [paper][code]
- Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks (AAAI, 2023) [paper][code]
- Hidden Markov Models for Temporal Graph Representation Learning (ESANN, 2023) [paper][code]
- 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]
- Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift (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 (WWW, 2022) [paper][code]
- Neural Predicting Higher-order Patterns in Temporal Networks (WWW, 2022) [paper][code]
- TREND: TempoRal Event and Node Dynamics for Graph Representation Learning (WWW, 2022) [paper][code]
- A Viral Marketing-Based Model For Opinion Dynamics in Online Social Networks (WWW, 2022) [paper]
- 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]
- 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 (WWW, 2021) [paper][code]
- TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks (WWW, 2021) [paper]
- 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]
- 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 (WWW, 2020) [paper][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]
- 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 (WWW, 2019) [paper]
- Real-Time Streaming Graph Embedding Through Local Actions (WWW, 2019) [paper]
- 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]
- 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 (WWW, 2018) [paper][code]
- Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding (IJCAI, 2018) [paper]