NeuraLSP: An Efficient and Rigorous Neural Left Singular Subspace Preconditioner for Conjugate Gradient Methods | ScienceToStartup | ScienceToStartup

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References (42)

[1]

Chiral rank-$k$ truncations for the multigrid preconditioner of Wilson fermions in lattice QCD

2025Travis Whyte, Andreas Stathopoulos et al.

[2]

Operator SVD with Neural Networks via Nested Low-Rank Approximation

2024J. J. Ryu, Xiangxiang Xu et al.

[3]

PyAMG: Algebraic Multigrid Solvers in Python

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"NeuraLSP provides an efficient neural preconditioning method for faster PDE solutions, promising significant speed improvements for scientific computing."

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NeuraLSP: An Efficient and Rigorous Neural Left Singular Subspace Preconditioner for Conjugate Gradient Methods

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Founder's Pitch

"NeuraLSP provides an efficient neural preconditioning method for faster PDE solutions, promising significant speed improvements for scientific computing."

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NeuraLSP: An Efficient and Rigorous Neural Left Singular Subspace Preconditioner for Conjugate Gradient Methods

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Founder's Pitch

"NeuraLSP provides an efficient neural preconditioning method for faster PDE solutions, promising significant speed improvements for scientific computing."

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