Six popular machine learning models. (a) Decision tree; (b) feedforward neural network (Trans: transformation; Activ Func: activation functions); (c) convolution neural network (Conv: convolution; ...
By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...
(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...
Peer-reviewed research finds the company’s novel technology enables faster dataset construction, further shortening Avicenna’s timelines to develop life-saving medicines. “We’re accustomed to hearing ...
In March, a paper in the Journal of the American Chemical Society sparked a heated Twitter debate on the value of machine learning for predicting optimal reaction pathways in synthetic chemistry. The ...
Machine-learning tools have taken us closer to understanding electrons and how they behave in chemical interactions, following news that UK-based AI company DeepMind, owned by Google’s parent company ...
A new machine learning tool can calculate the energy required to make -- or break -- simple molecules with higher accuracy than conventional methods. Extensions to more complicated molecules may help ...
Much of the analytical work performed by physical chemists requires the use of sophisticated instrumentation and equipment. This article will provide a brief overview of the analytical instruments ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results