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浏览/检索结果: 共5条，第1-5条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Machine Learning Methods in Solving the Boolean Satisfiability Problem 期刊论文 Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 640-655 作者:  Wenxuan Guo 收藏  |  浏览/下载：0/0  |  提交时间：2023/09/25 Machine learning (ML), Boolean satisfiability (SAT), deep learning, graph neural networks (GNNs), combinatorial optimization   Structure-Aware Prototypical Neural Process for Few-Shot Graph Classification 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15 作者:  Lin, Xixun;  Li, Zhao;  Zhang, Peng;  Liu, Luchen;  Zhou, Chuan 收藏  |  浏览/下载：14/0  |  提交时间：2023/02/07 Task analysis  Kernel  Training  Decoding  Stochastic processes  Predictive models  Computational modeling  Few-shot learning  graph classification  graph neural networks (GNNs)  neural process (NP)   Sampling Methods for Efficient Training of Graph Convolutional Networks: A Survey 期刊论文 IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 2, 页码: 205-234 作者:  Xin Liu;  Mingyu Yan;  Lei Deng;  Guoqi Li;  Xiaochun Ye 收藏  |  浏览/下载：52/0  |  提交时间：2021/11/03 Efficient training  graph convolutional networks (GCNs)  graph neural networks (GNNs)  sampling method   GPENs: Graph Data Learning With Graph Propagation-Embedding Networks 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14 作者:  Jiang, Bo;  Wang, Leiling;  Cheng, Jian;  Tang, Jin;  Luo, Bin 收藏  |  浏览/下载：26/0  |  提交时间：2022/01/27 Task analysis  Computer architecture  Semisupervised learning  Deep learning  Laplace equations  Data models  Labeling  Graph embedding  graph neural networks (GNNs)  graph propagation  semi-supervised learning   Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Liu, Yixin;  Li, Zhao;  Pan, Shirui;  Gong, Chen;  Zhou, Chuan 收藏  |  浏览/下载：4/0  |  提交时间：2022/04/02 Anomaly detection  Task analysis  Graph neural networks  Unsupervised learning  Predictive models  Pattern matching  Training  Anomaly detection  attributed networks  contrastive self-supervised learning  graph neural networks (GNNs)  unsupervised learning