SemiH: DFT Hamiltonian neural network training with semi-supervised learning
Y Cho, G Choi, G Ham, M Shin… - … Learning: Science and …, 2024 - iopscience.iop.org
Over the past decades, density functional theory (DFT) calculations have been utilized in
various fields such as materials science and semiconductor devices. However, due to the …
various fields such as materials science and semiconductor devices. However, due to the …
Active Learning for Graph Neural Networks Training in Catalyst Energy Prediction
Y Sakai, N Matsumura, A Inoue… - … Joint Conference on …, 2024 - ieeexplore.ieee.org
The electrification of major industrial processes constitutes an important step in reducing
global carbon emissions. Thus, the identification of materials able to serve as catalysts for …
global carbon emissions. Thus, the identification of materials able to serve as catalysts for …
An Analysis of the Effect of the Replacement Ratio in the Pre-training SSL Phase on the Accuracy of Models after Fine-Tuning
L Daniele, D Thang - 人工知能学会研究会資料 人工知能基本問題研究 …, 2024 - jstage.jst.go.jp
Training a model in a scarce data context is not an easy task, but high accuracy can be
reached by fine-tuning a pre-trained model. When dealing with molecules, the pre-training …
reached by fine-tuning a pre-trained model. When dealing with molecules, the pre-training …