WF-Bench is a new benchmark for neural network wavefunctions that matches them to diverse quantum many-body targets and derives empirical scaling laws for representability based on system size and model parameters like determinant count and depth.
Erwin: A tree-based hierarchical transformer for large-scale phys- ical systems.arXiv preprint arXiv:2502.17019,
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ML surrogates accurately emulate single steps of simplified thrombectomy simulations with speedups but lack stability over long times with complex geometries.
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WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws
WF-Bench is a new benchmark for neural network wavefunctions that matches them to diverse quantum many-body targets and derives empirical scaling laws for representability based on system size and model parameters like determinant count and depth.
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An Exploratory Study into using Machine-Learning for Fast Step-by-step Emulation of Numerical Mechanical Thrombectomy Simulations for Ischemic Stroke
ML surrogates accurately emulate single steps of simplified thrombectomy simulations with speedups but lack stability over long times with complex geometries.