2 citations · 3 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2024★ 2 cited
Leveraging Domain Adaptation for Accurate Machine Learning Predictions of New Halide Perovskites
Dipannoy Das Gupta, Zachary J. L. Bare, Suxuen Yew +5
We combine graph neural networks (GNN) with an inexpensive and reliable structure generation approach based on the bond-valence method (BVM) to train accurate machine learning mode…
cond-mat.mtrl-sci2023★ 1 cited
Interpretable machine learning to understand the performance of semi local density functionals for materials thermochemistry
Santosh Adhikari, Christopher J. Bartel, Christopher Sutton
This study investigates the use of machine learning (ML) to correct the enthalpy of formation (Hf) from two separate DFT functionals, PBE and SCAN, to the experimental Hf across 10…