接着使用BERT学习词嵌入,这个嵌入被用来初始化图中节点的嵌入。构建的三个图数据集为Graph-SST2、Graph-SST5和Graph-Twitter,这三个数据集很快公布,数据集的统计数据在上面的表中。表中还体现了一些模型在这数据集上的预测精度。 分子数据也被广泛应用于解释任务。比如MUTAG、BBBP和Tox21。每一个这样的数据集都...
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions 3. 快速浏览通道:思维导图 如果看不清楚的话可以去评论区下载源文件~ 1. Intro 1.1 推荐算法发展历史 1.1.1 Shallow Models 协同过滤CF,代表方法矩阵分解MF 《Matrix factorization techniques for recommender systems...
Neural architecture search: A survey J. Mach. Learn. Res., 20 (55) (2019), pp. 1-21 View in ScopusGoogle Scholar [65] Holzinger A., Malle B., Saranti A., Pfeifer B. Towards multi-modal causability with graph neural networks enabling information fusion for explainable AI Inf. Fusion...
in our survey, we focus more on the methods in emerging directions such as scalable attacks, graph backdoor attacks and recent defense methods. More specifically, perturbation sampling and perturbation candidate reduction are two directions that have been explored to improve the...
First, the concepts and common methods of explainable artificial intelligence (xAI) and knowledge tracing are introduced. Next, explainable knowledge tracing (xKT) models are classified into two categories: transparent models and "black box" models. Then, the interpretable methods used are reviewed ...
graph neural networks (GNN) have shown to be useful, providing a possibility to process data with graph-like properties in the framework of artificial neural networks (ANN)14. Motivated by their success in computer vision15,16, convolution operations were recently extended to the graph domain17,...
We present a survey of ways in which existing scientific knowledge are included when constructing models with neural networks. The inclusion of domain-knowledge is of special interest not just to constructing scientific assistants, but also, many other a
A Survey of the State of Explainable AI for Natural Language Processing. AACL 2020 paper bib Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis, Ban Kawas, Prithviraj Sen A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images. arXiv 2020 paper ...
A detailed survey of explainable deep learning for efficient and robust pattern recognition is represented. • Explainable methods fordeep neural networks, including visualization and uncertainty estimation, are categorized and presented. • Model compression and acceleration methods for efficient deep lear...
Next, we introduce KDG preliminaries including graph neural networks and knowledge distillation, formally define theproblem, and discuss two objectives of KDG. 接下来,我们介绍了 KDG 预备知识,包括图神经网络和知识蒸馏,正式定义问题并讨论 KDG 的两个目标。