Deep learning-based surrogate models outperform simulators and could hasten scientific discoveries

Surrogate models supported by neural networks can perform as well, and in some ways better, than computationally expensive simulators and could lead to new insights in complicated physics problems such as inertial confinement fusion (ICF), Lawrence Livermore National Laboratory (LLNL) scientists reported.

from News on Artificial Intelligence and Machine Learning https://ift.tt/30VzpLt
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