The penetration of renewable energy resources (RES) generation and the interconnection of
regional power grids in wide area and large scale have led the modern power system to …

Recently, the emergence of pre-trained models (PTMs) has brought natural language
processing (NLP) to a new era. In this survey, we provide a comprehensive review of PTMs …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Graphs naturally appear in numerous application domains, ranging from social analysis,
bioinformatics to computer vision. The unique capability of graphs enables capturing the …

Deep learning has revolutionized many machine learning tasks in recent years, ranging
from image classification and video processing to speech recognition and natural language …

Lots of learning tasks require dealing with graph data which contains rich relation
information among elements. Modeling physics systems, learning molecular fingerprints …

Deep learning on graphs has become one of the hottest topics in machine learning. The
book consists of four parts to best accommodate our readers with diverse backgrounds and …

The adaptive processing of graph data is a long-standing research topic that has been lately
consolidated as a theme of major interest in the deep learning community. The snap …

Aspect-level sentiment classification is a fundamental subtask of fine-grained sentiment
analysis. The syntactic information and commonsense knowledge are important and useful …

The emergence of various social networks has generated vast volumes of data. Efficient
methods for capturing, distinguishing, and filtering real and fake news are becoming …