In the last few years, we have seen the transformative impact of deep learning in many applications, particularly in speech recognition and computer vision. Inspired by Google's Inception-ResNet deep convolutional neural network (CNN) for image classification, we have developed "Chemception", a deep CNN for the predict…
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Deep learning models can predict chemical properties without needing advanced chemistry knowledge.
problem How much chemistry does a deep neural network need to know to make accurate predictions?
method Systematically removing and adding localized domain-specific information to image channels of training data.
result An augmented Chemception (AugChemception) outperforms the original model in predicting toxicity, activity, and solvation free energy.
ChemNet uses rule-based labels for weakly supervised learning to predict chemical properties.
problem Lack of labeled data in chemistry.
method Rule-based knowledge for training ChemNet, a deep neural network, on large unlabeled chemical databases.
result ChemNet outperforms DNN models trained with conventional supervised learning on smaller datasets.