activity
20172022
most citedAn adsorbed gas estimation model for shale gas reservoirs via statistical learning

74 citations · 123 across the 5 of their papers we have counts for

collaborators

8 papers

cs.LG20222 cited

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.…

cs.LG20221 cited

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…

cs.AI202234 cited

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…

cs.LG2021

Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method

Yuntian Chen, Dou Huang, Dongxiao Zhang +4

Machine learning models have been successfully used in many scientific and engineering fields. However, it remains difficult for a model to simultaneously utilize domain knowledge…

eess.SP202012 cited

Physics-constrained indirect supervised learning

Yuntian Chen, Dongxiao Zhang

This study proposes a supervised learning method that does not rely on labels. We use variables associated with the label as indirect labels, and construct an indirect physics-cons…

eess.SP2020

Ensemble long short-term memory (EnLSTM) network

Yuntian Chen, Dongxiao Zhang

In this study, we propose an ensemble long short-term memory (EnLSTM) network, which can be trained on a small dataset and process sequential data. The EnLSTM is built by combining…