2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
Sohei Arisaka, Qianxiao Li
Scientific computing is an essential tool for scientific discovery and engineering design, and its computational cost is always a main concern in practice. To accelerate scientific…
math.NA2024★ 2 cited
Mitigating distribution shift in machine learning-augmented hybrid simulation
Jiaxi Zhao, Qianxiao Li
We study the problem of distribution shift generally arising in machine-learning augmented hybrid simulation, where parts of simulation algorithms are replaced by data-driven surro…
math.NA2022
Principled Acceleration of Iterative Numerical Methods Using Machine Learning
Sohei Arisaka, Qianxiao Li
Iterative methods are ubiquitous in large-scale scientific computing applications, and a number of approaches based on meta-learning have been recently proposed to accelerate them.…