Mar 25, 2020 · Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for Crystals. Juhwan Noh. Juhwan Noh.
Mar 25, 2020 · The proposed hybrid model reduces the required DFT calculations by a factor of >50 compared to the previous DFT-HTS in making the same discovery ...
Our model is built upon existing crystal graph convolutional neural network (CGCNN) to obtain formation energy of a crystal structure but is modified to allow ...
Uncertainty-Quantified Hybrid Machine Learning/Density ... - OUCI
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Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for Crystals ; Journal: Journal of Chemical Information ...
Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for Crystals. J. Noh, G. Gu, S. Kim, and Y. Jung.
Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for Crystals. Overview of attention for article ...
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Oct 6, 2020 · Prof. Yousung Jung's group has developed a new accelerated high throughput screening (HTS) method using uncertainty-quantified machine ...
Uncertainty-quantified hybrid machine learning/density functional theory high throughput screening method for crystals. J Noh, GH Gu, S Kim, Y Jung. Journal ...
Apr 16, 2024 · High-throughput hybrid-functional DFT calculations of bandgaps and formation energies and multifidelity learning with uncertainty quantification.
Missing: Screening Crystals.