4 citations · 6 across the 4 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 1 cited
Multimodal machine learning for materials science: composition-structure bimodal learning for experimentally measured properties
Sheng Gong, Shuo Wang, Taishan Zhu +2
The widespread application of multimodal machine learning models like GPT-4 has revolutionized various research fields including computer vision and natural language processing. Ho…
cond-mat.mtrl-sci2023★ 4 cited
Correlated Terahertz phonon-ion interactions control ion conduction in a solid electrolyte
Kim H. Pham, Kiarash Gordiz, Natan A. Spear +9
Ionic conduction in solids that exceeds 1 mS/cm is predicted to involve coupled phonon-ion interactions in the crystal lattice. Here, we use theory and experiment to measure the po…
cond-mat.mtrl-sci2021
Calibrating DFT formation enthalpy calculations by multi-fidelity machine learning
Sheng Gong, Shuo Wang, Tian Xie +3
Machine learning materials properties measured by experiments is valuable yet difficult due to the limited amount of experimental data. In this work, we use a multi-fidelity random…