Lucas MacQuarrie, Data driven governing equations approximation using deep neural networks

We will discuss about “Data driven governing equations approximation using deep neural networks” Journal of Computational Physics (2019). Abstract We present a numerical framework for approximating unknown governing equations using observation data and deep neural networks (DNN). In particular, we propose to use residual network (ResNet) as the basic building block for equation approximation. We demonstrate that the ResNet block can be

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