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Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Big Data in Online Social Networks: User Interaction Analysis to Model User Behavior in Social Networks
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Complex Interactions in Social and Event Network Analysis
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Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback
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Graph embedding techniques, applications, and performance: A survey
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Analyzing the Creative Editing Behavior of Wikipedia Editors
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Deep Dynamic Network Embedding for Link Prediction
inferredcites →https://doi.org/10.1109/tcss.2014.2307453openalex-snapshot
Modeling Temporal Activity Patterns in Dynamic Social Networks
inferredcites →https://doi.org/10.1109/tkde.2016.2591009openalex-snapshot
Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks
inferredcites →https://doi.org/10.1117/12.280797openalex-snapshot
New extension of the Kalman filter to nonlinear systems
inferredcites →https://doi.org/10.1137/1.9781611973440.33openalex-snapshot
A Deep Learning Approach to Link Prediction in Dynamic Networks
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Exploiting temporal influence in online recommendation
inferredcites →https://doi.org/10.1145/2939672.2939875openalex-snapshot
Recurrent Marked Temporal Point Processes
inferredcites →https://doi.org/10.1145/3018661.3018689openalex-snapshot
Recurrent Recommender Networks
inferredcites →https://doi.org/10.1145/3041021.3054198openalex-snapshot
Predicting Intent Using Activity Logs
inferredcites →https://doi.org/10.1145/3097983.3097997openalex-snapshot
Patient Subtyping via Time-Aware LSTM Networks
inferredcites →https://doi.org/10.1145/3110025.3116209openalex-snapshot
Combining structural and dynamic information to predict activity in link streams
inferredcites →https://doi.org/10.1145/3132847.3132918openalex-snapshot
Learning Node Embeddings in Interaction Graphs
inferredcites →https://doi.org/10.1145/3132847.3132919openalex-snapshot
Attributed Network Embedding for Learning in a Dynamic Environment
inferredcites →https://doi.org/10.1145/3159652.3159706openalex-snapshot
Network Embedding as Matrix Factorization
inferredcites →https://doi.org/10.1145/3178876.3186141openalex-snapshot
Community Interaction and Conflict on the Web
inferredcites →https://doi.org/10.1145/3184558.3191526openalex-snapshot
Continuous-Time Dynamic Network Embeddings
inferredcites →https://doi.org/10.1145/3285029openalex-snapshot
Deep Learning Based Recommender System
inferredcites →https://doi.org/10.1145/3308558.3313633openalex-snapshot
The Block Point Process Model for Continuous-time Event-based Dynamic Networks
inferredcites →https://doi.org/10.1145/3308558.3313747openalex-snapshot
Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems
inferredcites →https://doi.org/10.1609/icwsm.v12i1.15059openalex-snapshot
Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks
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Predicting interactions between individuals with structural and dynamical information
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MOOCs: A systematic study of the published literature 2008-2012
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Predicting MOOC Dropout over Weeks Using Machine Learning Methods
inferredcites →https://doi.org/10.48550/arxiv.1507.02293openalex-snapshot
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
inferredcites →https://doi.org/10.48550/arxiv.1705.05742openalex-snapshot
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
inferredcites →https://doi.org/10.48550/arxiv.1709.05584openalex-snapshot
Representation Learning on Graphs: Methods and Applications
inferredcites →https://doi.org/10.48550/arxiv.1804.05755openalex-snapshot
DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Text meets topology: A dynamic graph learning method with Dy-GNNs and LLMs for tracking text attributed community evolution in complex networks
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Structural–Temporal embedding of large-scale dynamic networks with parallel implementation
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Attention-based dynamic multilayer graph neural networks for loan default prediction
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A short-term power forecasting method for wind farm clusters considering feature enhancement and real-time optimization of dynamic graphs
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Dynamic graph neural network with historic-sequential information representation
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Uncertainty-aware dynamic graph contrastive learning for node classification and anomaly detection
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LGSA: A next POI prediction method by using local and global interest with spatiotemporal awareness
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Balancing structure and position information in Graph Transformer network with a learnable node embedding
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Dynamic recommender system for chronic disease-focused online health community
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Dynamic heterogeneous graph representation based on adaptive negative sample mining via high-fidelity instances and context-aware uncertainty learning
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Coformer for session-based recommendation with dual positional information
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TPCA-GAD: Topology preference-consistency aggregation for zero-shot graph anomaly detection
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High-performance temporal hypergraph neural network with multi-head attention for link prediction in dynamic networks
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Adversarial attacks against dynamic graph neural networks via node injection
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Rethinking multi-level information fusion in temporal graphs: Pre-training then distilling for better embedding
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Fusion3M: Community-based multi-scale co-evolving network for dynamic graph representation learning
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Generating evolving region embedding with memory-based graph for dynamic urban sensing
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To change or not to change? Modeling software system interactions using Temporal Graphs and Graph Neural Networks: A focus on change propagation
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An event-driven dynamic graph learning framework with large-scale cellular signaling streams
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TAAD: Time-varying adversarial anomaly detection in dynamic graphs
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Graph anomaly detection via local contrastive learning and attribute reconstruction
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110850openalex-snapshot
TI-MVD: A temporal interaction-enhanced model for malware variants detection
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Stable distance of persistent homology for dynamic graph comparison
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Learning dynamic embeddings for temporal attributed networks
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BP-MoE: Behavior Pattern-aware Mixture-of-Experts for Temporal Graph Representation Learning
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112452openalex-snapshot
Temporal Graph Network for continuous-time dynamic event sequence
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Synthesizing global and local perspectives in contrastive learning for graph anomaly detection
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.113904openalex-snapshot
Capturing latent evolution in dynamic graph: A dual-view architecture from spectral perspective
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DyAtGNN: Dynamic Attention Graph Neural Networks for dynamic graph
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PDCE: A Plug-and-Play Dual-Channel Enhancement framework for Dynamic Graph Neural Networks
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TDiscNet: Topological discrepancy-guided adaptive semantic modeling for dynamic text-attributed graphs
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Bridging dynamics and semantics: A unified perspective on explainable Graph Neural Networks based stream reasoning
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HGLD-STRec: A Hyperbolic Global–Local Dynamic Evolution Framework for Spatio-Temporal Recommendation
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HyperDNE: Enhanced hypergraph neural network for dynamic network embedding
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DyTSCL: Dynamic graph representation via tempo-structural contrastive learning
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Multi-relational dynamic graph representation learning
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Contrastive Hawkes graph neural networks with dynamic sampling for event prediction
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Memory-based walk-enhanced dynamic graph neural network for temporal graph representation learning
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Dynamic heterogeneous graph contrastive learning based on multi-prior tasks
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A learnable sampling method for scalable graph neural networks
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TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers
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ConTIG: Continuous representation learning on temporal interaction graphs
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Towards a better negative sampling strategy for dynamic graphs
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Learning dynamic graph representations through timespan view contrasts
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Frequency Self-Adaptation Graph Neural Network for Unsupervised Graph Anomaly Detection
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Dynamic Graph Contrastive Learning via Maximize Temporal Consistency
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SiGNN: A spike-induced graph neural network for dynamic graph representation learning
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Advancing evolution characterization in dynamic networks: A quantum walk and thermodynamics perspective
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Higher-order Enhanced Contrastive-based Graph Anomaly Detection Without Graph Augmentation
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TGFormer: Towards temporal graph transformer with auto-correlation mechanism
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Ethereum phishing fraud detection via dynamic graph neural network with anonymous walks
inferred← citeshttps://doi.org/10.1016/j.patcog.2026.114538openalex-snapshot
EEdgeGNN: A local enhanced dynamic graph neural network with edge change perception
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HAPO: Hierarchical affinity aware propagation for unsupervised graph anomaly detection
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Multiple Order Local Information model for link prediction in complex networks
inferred← citeshttps://doi.org/10.1016/j.rcim.2025.103214openalex-snapshot
3DprintMIND: An AI-Agent system using large language models and dynamic manufacturing knowledge graphs for smart manufacturing
inferred← citeshttps://doi.org/10.1038/s41562-025-02251-0openalex-snapshot
Charting multidimensional ideological polarization across demographic groups in the USA
inferred← citeshttps://doi.org/10.1038/s41597-025-04595-8openalex-snapshot
A Temporal Graph Dataset of Bitcoin Entity-Entity Transactions
inferred← citeshttps://doi.org/10.1038/s41598-023-50977-6openalex-snapshot
Dynamic network link prediction with node representation learning from graph convolutional networks
inferred← citeshttps://doi.org/10.1038/s41598-024-56226-8openalex-snapshot
Dynamic identification of important nodes in complex networks based on the KPDN–INCC method
inferred← citeshttps://doi.org/10.1038/s41598-026-37640-6openalex-snapshot
Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning
inferred← citeshttps://doi.org/10.1039/d1cp03622jopenalex-snapshot
RPnet: a reverse-projection-based neural network for coarse-graining metastable conformational states for protein dynamics
inferred← citeshttps://doi.org/10.1080/10447318.2024.2400413openalex-snapshot
Exploring Pedagogical Dynamics via Teachers’ Interactions with Digital Textbook Platforms
inferred← citeshttps://doi.org/10.1109/acait67930.2025.11522652openalex-snapshot
RHGAN: A Relation-Aware Heterogeneous Graph Attention Network for Recommendation
inferred← citeshttps://doi.org/10.1109/access.2020.3037118openalex-snapshot
Network Representation Learning: From Traditional Feature Learning to Deep Learning
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Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey
inferred← citeshttps://doi.org/10.1109/access.2021.3114099openalex-snapshot
An Overview of Fairness in Clustering
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A Robust Comparative Analysis of Graph Neural Networks on Dynamic Link Prediction
inferred← citeshttps://doi.org/10.1109/access.2022.3224816openalex-snapshot
Exploration in Sequential Recommender Systems via Graph Representations
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NFE-PCN: A Node Feature Enhanced Embedding Framework for Pattern Change in Dynamic Network
inferred← citeshttps://doi.org/10.1109/access.2023.3305945openalex-snapshot
Matrix Completion of Adaptive Jumping Graph Neural Networks for Recommendation Systems
inferred← citeshttps://doi.org/10.1109/access.2024.3378111openalex-snapshot
Dynamic Graph Representation Learning With Neural Networks: A Survey
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Unsupervised Inductive Node Representation Learning for Dynamic Graphs
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