HotRelax is a high-order tensor message-passing neural network trained on paired unrelaxed-relaxed structures to predict relaxed crystal geometries in a single forward pass without force labels or iteration.
Gemnet: Universal directional graph neural networks for molecules
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Spatial statistics on voxelized structures using FFT correlations and PCA yield low-dimensional convex features that support accurate predictions with as few as 10 training samples.
mlip v2 is a new software release that integrates API redesign, e3j backend, eSEN model, improved charge modeling, and expanded simulation capabilities to support larger-scale molecular modeling.
citing papers explorer
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High-order tensor neural network for iteration-free structure relaxation
HotRelax is a high-order tensor message-passing neural network trained on paired unrelaxed-relaxed structures to predict relaxed crystal geometries in a single forward pass without force labels or iteration.
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Spatial statistics for screening molecular structures
Spatial statistics on voxelized structures using FFT correlations and PCA yield low-dimensional convex features that support accurate predictions with as few as 10 training samples.
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Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation
mlip v2 is a new software release that integrates API redesign, e3j backend, eSEN model, improved charge modeling, and expanded simulation capabilities to support larger-scale molecular modeling.