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The application of modern machine learning to challenges in atomistic simulation is gaining attraction. We present new machine learning models that can predict the energy of the oxidative addition process between a transition metal complex and a substrate ...
The fast and reliable determination of wave functions and electron densities of macromolecules has been one of the goals of theoretical chemistry for a long time, and in this context, several linear scaling techniques have been successfully devised over th ...
AMER CHEMICAL SOC2018
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How membrane receptors transduce external signals across the membrane and activate intracellular processes is a key question for fundamental research and for therapeutic purposes. Reliable in situ investigations requiest to preserve the full biological act ...
In this account, we demonstrate how statistical learning approaches can be leveraged across a range of different quantum chemical areas to transform the scaling, nature, and complexity of the problems that we are tackling. Selected examples illustrate the ...