21 citations · 31 across the 8 of their papers we have counts for
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Surprisingly High Redundancy in Electronic Structure Data Across Materials Explained by Low Intrinsic Dimensionality
Sazzad Hossain, Ponkrshnan Thiagarajan, Shashank Pathrudkar +4
Machine learning (ML) models for electronic structure typically rely on large datasets generated by computationally expensive Kohn-Sham density functional theory calculations, as i…
Electronic structure prediction of medium and high entropy alloys across composition space
Shashank Pathrudkar, Stephanie Taylor, Abhishek Keripale +6
We propose machine learning (ML) models to predict the electron density -- the fundamental unknown of a material's ground state -- across the composition space of concentrated allo…
Electronic Structure Prediction of Multi-million Atom Systems Through Uncertainty Quantification Enabled Transfer Learning
Shashank Pathrudkar, Ponkrshnan Thiagarajan, Shivang Agarwal +2
The ground state electron density -- obtainable using Kohn-Sham Density Functional Theory (KS-DFT) simulations -- contains a wealth of material information, making its prediction v…