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cs.LG2022★ 20 cited
Comparison of neural closure models for discretised PDEs
Hugo Melchers, Daan Crommelin, Barry Koren +2
Neural closure models have recently been proposed as a method for efficiently approximating small scales in multiscale systems with neural networks. The choice of loss function and…
cs.LG2022
On the influence of stochastic roundoff errors and their bias on the convergence of the gradient descent method with low-precision floating-point computation
Lu Xia, Stefano Massei, Michiel E. Hochstenbach +1
When implementing the gradient descent method in low precision, the employment of stochastic rounding schemes helps to prevent stagnation of convergence caused by the vanishing gra…