Moving from correlation to causation is especially important when it comes to understanding the conditions under which a machine learning model may fail, how long we can expect it to continue ...

Machine-learned electron correlation model based on frozen core approximation. The Journal of Chemical Physics 2020, 153 (18) ... Machine learning exchange-correlation potential in time-dependent ...

Grad DFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques. The library provides significant ...

Tunnelling through steel reinforced concrete piles using shield machine involves high risk and creates an engineering challenge. Protecting safety of the superstructure is beneficial for the success ...

The accuracy of machine learning depends largely on the quantity and quality of the training data. However, it is generally difficult to prepare a large number of high-quality data. To generate ...

My mission is to build a machine learning model that can calculate what makes a good Ars headline. And by "good," I mean one that appeals to you, dear Ars reader.