76 citations · 125 across the 6 of their papers we have counts for
6 papers
Crack-Net: Prediction of Crack Propagation in Composites
Hao Xu, Wei Fan, Ambrose C. Taylor +3
Computational solid mechanics has become an indispensable approach in engineering, and numerical investigation of fracture in composites is essential as composites are widely used…
Retention Time Prediction for Chromatographic Enantioseparation by Quantile Geometry-enhanced Graph Neural Network
Hao Xu, Jinglong Lin, Dongxiao Zhang +1
A new research framework is proposed to incorporate machine learning techniques into the field of experimental chemistry to facilitate chromatographic enantioseparation. A document…
TgDLF2.0: Theory-guided deep-learning for electrical load forecasting via Transformer and transfer learning
Jiaxin Gao, Wenbo Hu, Dongxiao Zhang +1
Electrical energy is essential in today's society. Accurate electrical load forecasting is beneficial for better scheduling of electricity generation and saving electrical energy.…
AutoKE: An automatic knowledge embedding framework for scientific machine learning
Mengge Du, Yuntian Chen, Dongxiao Zhang
Imposing physical constraints on neural networks as a method of knowledge embedding has achieved great progress in solving physical problems described by governing equations. Howev…
Semantic interpretation for convolutional neural networks: What makes a cat a cat?
Hao Xu, Yuntian Chen, Dongxiao Zhang
The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the "black box" model. Fundament…
Integration of knowledge and data in machine learning
Yuntian Chen, Dongxiao Zhang
Scientific research's mandate is to comprehend and explore the world, as well as to improve it based on experience and knowledge. Knowledge embedding and knowledge discovery are tw…