Neural networks in chemistry

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Artificial neural networks for computer-based molecular design. (1998, methodology): “For small molecules fast 3D structure generators based on 2D representations are at hand which allows 3D descriptors to be derived if no experimental spatial structures are available (Sadowski and Gasteiger, 1993, 1994).”
Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns (2019, methodology): “It should be noted the use data from large repositories (e.g., Protein Data Bank and Cambridge Structural Database) and ML methods are not new (Hiller et al., 1973; Gasteiger and Zupan, 1993; Behler, 2016).”
Neural network studies, 1. Comparison of overfitting and overtraining (1995, methodology): “During the optimization procedure of the network, the mean square error (MSE) is used as a criterion of network training (1) x ( Y i”