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Dynamic Link Prediction
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
A PID-Controlled Tensor Wheel Decomposition Model for Dynamic Link Prediction
Predict Confidently, Predict Right: Abstention in Dynamic Graph Learning
Supra-Laplacian Encoding for Transformer on Dynamic Graphs
Dynamic Link and Flow Prediction in Bank Transfer Networks
Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks
DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
DyGMamba: Efficiently Modeling Long-Term Temporal Dependency on Continuous-Time Dynamic Graphs with State Space Models
Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction
Temporal receptive field in dynamic graph learning: A comprehensive analysis
From Link Prediction to Forecasting: Information Loss in Batch-based Temporal Graph Learning
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms
Enhancing Cross-domain Link Prediction via Evolution Process Modeling
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers
Exploring Time Granularity on Temporal Graphs for Dynamic Link Prediction in Real-world Networks
Dynamic Link Prediction for New Nodes in Temporal Graph Networks
Dynamic Graph Representation Learning via Edge Temporal States Modeling and Structure-reinforced Transformer
Towards Better Dynamic Graph Learning: New Architecture and Unified Library
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning
DBGDGM: Dynamic Brain Graph Deep Generative Model
DyG2Vec: Efficient Representation Learning for Dynamic Graphs
DyCSC: Modeling the Evolutionary Process of Dynamic Networks Based on Cluster Structure
Towards Better Evaluation for Dynamic Link Prediction
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Dyn-Backdoor: Backdoor Attack on Dynamic Link Prediction
Learning Representation over Dynamic Graph using Aggregation-Diffusion Mechanism
A Survey on Embedding Dynamic Graphs
GRADE: Graph Dynamic Embedding
Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey
Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions
Variational Graph Recurrent Neural Networks
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning
Canonical Tensor Decomposition for Knowledge Base Completion
Representation Learning over Dynamic Graphs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.