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您的检索式：作者名="Sergei.V.Kalinin"
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| 1 | Off-the-shelf deep learning is not enough,and requires parsimony,Bayesianity,and causality显示文摘Deep neural networks(‘deep learning’)have emerged as a technology of choice to tackle problems in speech recognition,computer vision,finance,etc.However,adoption of deep learning in physical domains brings substantial challenges stemming from the correlative nature of deep learning methods compared to the causal,hypothesis driven nature of modern science.We argue that the broad adoption of Bayesian methods incorporating prior knowledge,development of solutions with incorporated physical constraints and parsimonious structural descriptors and generative models,and ultimately adoption of causal models,offers a path forward for fundamental and applied research. | Rama K.Vasudevan Maxim Ziatdinov Lukas Vlcek Sergei.V.Kalinin | 2021 | npj Computational Materials2021，，1： | 2 |
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