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Found 6 papers, 1 papers with code
GraphEdit: Large Language Models for Graph Structure Learning
Graph Structure Learning (GSL) focuses on capturing intrinsic dependencies and interactions among nodes in graph-structured data by generating novel graph structures.
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
Moreover, we theoretically establish that the number of distinguishable eigenvalues plays a pivotal role in determining the expressive power of spectral graph neural networks.
Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection
Massive captured face images are stored in the database for the identification of individuals.
Controllability of Multilayer Networked Sampled-data Systems
This paper explores the state controllability of multilayer networked sampled-data systems with inter-layer couplings, where zero-order holders (ZOHs) are on the control and transmission channels.
Controllability of Networked Sampled-data Systems
The controllability of networked sampled-data systems with zero-order holders on the control and transmission channels is explored, where single- and multi-rate sampling patterns are considered, respectively.
Channel Attention and Multi-level Features Fusion for Single Image Super-Resolution
Convolutional neural networks (CNNs) have demonstrated superior performance in super-resolution (SR).
