Abstract:<p>Deep
learning methods provide a novel way to establish a correlation between two
quantities. In this context, computer vision techniques like 3D-Convolutional
Neural Networks (3D-CNN) become a natural choice to associate a molecular
property with its structure due to the inherent three-dimensional nature of a
molecule. However, traditional 3D input data structures are intrinsically
sparse in nature, which tend to induce instabilities during the learning process,
which in turn may lead to under-fitted … Show more
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