Search Results for author:
Found 5 papers, 1 papers with code
Enhanced Urban Region Profiling with Adversarial Self-Supervised Learning
Urban region profiling is pivotal for smart cities, but mining fine-grained semantics from noisy and incomplete urban data remains challenging.
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning
Meanwhile, we design a supervised task to learn more robust representations and facilitate the contrastive learning process.
Multi-behavior Recommendation with SVD Graph Neural Networks
Graph Neural Networks (GNNs) have been extensively employed in the field of recommendation systems, offering users personalized recommendations and yielding remarkable outcomes.
Region-Wise Attentive Multi-View Representation Learning for Urban Region Embeddings
Our model focus on learn urban region representation from multi-source urban data.
Hybrid Augmented Automated Graph Contrastive Learning
Graph augmentations are essential for graph contrastive learning.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
