Deep Learning Chemistry: extracting chemical features from Graph Convolutional Neural Networks The task of quantum chemistry is to compute chemical properties of molecular compounds from the fundamental laws of quantum mechanics.  This poses a tremendous challenge as the most accurate

The curse of dimensionality and the blessings of sparsity and Monte Carlo sampling: From polynomial approximation to deep learning in high dimensions In data science and scientific computing, the approximation of high-dimensional functions from pointwise samples is a ubiquitous task,

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