MD17
PulseAugur coverage of MD17 — every cluster mentioning MD17 across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New method optimizes training data for machine-learned interatomic potentials
Researchers have developed a new method for selecting training data for machine-learned interatomic potentials, which are crucial for simulating materials at the atomic level. The study introduces a budget-dependent cro…
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FoldPipe system streamlines molecular ML data streaming
Researchers have developed FoldPipe, a Python orchestration layer designed to improve the efficiency of training molecular machine-learning models. This system addresses challenges with retrieving large molecular graph …
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New methods boost accuracy of interatomic potential models
Researchers have developed novel methods, Physics-Aware Neighborhood (PAN) pooling and Physics-Guided Spectral (PGS) mixers, to enhance the accuracy of short-range equivariant interatomic potentials. These techniques fo…
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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 AI Model Enhances Electronic Structure Calculations with SO(2) Frames
Researchers have developed QHNetV2, a novel neural network designed to efficiently predict Hamiltonian matrices for accelerating electronic structure calculations. The model achieves global SO(3) equivariance by utilizi…
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Orbital Transformers learn molecular wavefunctions for faster TDDFT simulations
Researchers have developed OrbEvo, an equivariant graph transformer model designed to predict molecular wavefunctions in time-dependent density functional theory (TDDFT). This new approach aims to accelerate the simulat…