Chuan Zhou

TL;DR: Irisin is secreted by muscle, increases with exercise, and mediates certain favorable effects of physical activity as discussed by the authors, however, the skeletal response to exercise is less clear, and the receptor for irisin has not been identified.

TL;DR: In this paper, the authors provide a systematic and comprehensive review of the contemporary deep learning techniques for graph anomaly detection, and highlight twelve extensive future research directions according to their survey results covering emerging problems introduced by graph data, anomaly detection and real applications.

TL;DR: This article summarizes the contributions of the various frameworks, models, and algorithms in each stream of deep learning in this domain along with the current challenges that remain unsolved and the future research opportunities yet to be explored.

TL;DR: Experiments on real-world datasets demonstrate that GraphNAS can design a novel network architecture that rivals the best human-invented architecture in terms of validation set accuracy and in a transfer learning task, it is observed that graph neural architectures designed by GraphNAS, when transferred to new datasets, still gain improvement in Terms of prediction accuracy.

TL;DR: Irisin is secreted by muscle, increases with exercise, and mediates certain favorable effects of physical activity as mentioned in this paper, however, the skeletal response to exercise is less clear, and the receptor for irisin has not been identified.