91 citations · 182 across the 11 of their papers we have counts for
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cs.LG2020★ 2 cited
Predicting the flow field in a U-bend with deep neural networks
Gergely Hajgató, Bálint Gyires-Tóth, György Paál
This paper describes a study based on computational fluid dynamics (CFD) and deep neural networks that focusing on predicting the flow field in differently distorted U-shaped pipes…
cs.LG2019★ 2 cited
Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks
Patrik Reizinger, Bálint Gyires-Tóth
The aim of this paper is to introduce two widely applicable regularization methods based on the direct modification of weight matrices. The first method, Weight Reinitialization, u…