QMugs
PulseAugur coverage of QMugs — every cluster mentioning QMugs across labs, papers, and developer communities, ranked by signal.
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New physics-aligned methods boost MLIP generalization
Researchers have developed new methods, OrthoNormal-Loss (ON-Loss) and Grassmann Restricted Occupied-Orbital Training (GROOT), to improve the generalization capabilities of machine-learned interatomic potentials (MLIPs)…
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New ML models improve electronic ground-state prediction with physics-aligned training
Researchers have developed new machine learning models for electronic ground-state prediction that significantly improve generalization capabilities beyond current methods. By incorporating physical constraints derived …
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New neural operator accelerates density functional theory calculations
Researchers have developed HamEvo, a novel neural operator designed to accelerate density functional theory (DFT) calculations by predicting Kohn-Sham Hamiltonians. This method achieves significant error reductions of 3…
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New SAIL method accelerates molecular simulations by over 2x
Researchers have developed a new method called Solver-Aligned Initialization Learning (SAIL) to improve the efficiency of self-consistent field (SCF) calculations in computational chemistry. Traditional machine learning…