Recently, there has been an increasing interest in deep graph similarity learning, where the key idea is to learn a deep learning model that maps input graphs to a target space such that the distance in the tar
2.Inductive Learning归纳学习,使用GCN+GAE等方式,多个模型结合,达到更好的效果3.Similarity Measures相似度衡量的方式,还可以优化,比如L2-reconstruction loss,拉普拉斯特征映射,和Wasserstein距离,选择一个合适的相似度衡量方式很重要。参考的内容:AE和VAE:https😕/blog.csdn.net/sinat_36197913/article/details/...
They are grouped into three main categories: explainable deep learning methods, efficient deep learning via model compression and acceleration, as well as robustness and stability in deep learning. For each of the three topics, a survey of the representative works and latest developments is presented...
which aims to project unimodal representations together into a shared semantic subspace such that the multimodal features can be fused; (ii) coordinated representation including cross-modal similarity models and canonical correlation analysis, which seeks to learn separated but constrained...
[197]作为先驱性的工作,首次提出了Similarity Group Proposal Network(SGPN)。该方法首先对每个点学习特征和语义map,接着引入相似度矩阵来表示各对点之间的相似度。为了学习到更多的判别式特征,使用了double-hinge loss来互相适应相似度矩阵和语义分割的结果。最后使用启发式的NMS方法将相似的点归并进一个实例中。由于...
We therefore carry out a systematic literature review on deep learning for anomaly detection in log data. Our main focus is thereby to survey scientific publications on the deployed model architectures, their respective requirements and transformations for handling unstructured input log data, the methods...
【论文泛读】《A Graph Similarity for Deep Learning》,题目期刊名/文献类型作者年份解决问题解决对策创新点论文不足下一步工作
Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation using deep learning techniques is presented. This paper makes two origin...
metric learning approaches learn by increasing the similarity between faces of same identity while decreasing the similarity between the faces of different identities. Regardless of the approach, all deep face supervisory signals are driven towards a single goal, inter-class discrepancy with intra-class...
Continual Graph Learning: A Survey 2023 Arxiv Towards Label-Efficient Incremental Learning: A Survey 2023 Arxiv Advancing continual lifelong learning in neural information retrieval: definition, dataset, framework, and empirical evaluation 2023 Arxiv How to Reuse and Compose Knowledge for a Lifetime of...