no code implementations • 23 Aug 2021 • Siddhant Agarwal, Nicola Tosi, Pan Kessel, Doris Breuer, Grégoire Montavon
Using a dataset of 10, 525 two-dimensional simulations of the thermal evolution of the mantle of a Mars-like planet, we show that deep learning techniques can produce reliable parameterized surrogates (i. e. surrogates that predict state variables such as temperature based only on parameters) of the underlying partial differential equations.
