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Found 4 papers, 3 papers with code
KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion
Knowledge graph completion (KGC) aims to alleviate the inherent incompleteness of knowledge graphs (KGs), which is a critical task for various applications, such as recommendations on the web.
Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction Prediction
To address this limitation, we propose BioKDN (Biomedical Knowledge Graph Denoising Network) for robust molecular interaction prediction.
Deep neural network based sparse measurement matrix for image compressed sensing
In this paper, a Deep neural network based Sparse Measurement Matrix (DSMM) is learned by the proposed convolutional network to reduce the sampling computational complexity and improve the CS reconstruction performance.
An End-to-End Compression Framework Based on Convolutional Neural Networks
The second CNN, named reconstruction convolutional neural network (RecCNN), is used to reconstruct the decoded image with high-quality in the decoding end.
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