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10/26/2022
Comparison of neural closure models for discretised PDEs
Neural closure models have recently been proposed as a method for effici...
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02/24/2022
On the influence of roundoff errors on the convergence of the gradient descent method with low-precision floating-point computation
The employment of stochastic rounding schemes helps prevent stagnation o...
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03/24/2021
A Simple and Efficient Stochastic Rounding Method for Training Neural Networks in Low Precision
Conventional stochastic rounding (CSR) is widely employed in the trainin...
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05/31/2020
Improved stochastic rounding
Due to the limited number of bits in floating-point or fixed-point arith...
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04/27/2020
Multi-level neural networks for PDEs with uncertain parameters
A novel multi-level method for partial differential equations with uncer...
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03/30/2020
Computing first passage times for Markov-modulated fluid models using numerical PDE problem solvers
A popular method to compute first-passage probabilities in continuous-ti...
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07/09/2019
