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How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?

, , , , and . WACV, page 1340-1349. IEEE Computer Society, (2018)

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Explanatory Masks for Neural Network Interpretability., , and . CoRR, (2019)Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction, , , and . (2017)cite arxiv:1712.02734Comment: Submitted to SIGKDD 2018.SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties., , , and . CoRR, (2017)IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks., , , and . IEEE BigData, page 1465-1473. IEEE, (2018)ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction., , , and . CoRR, (2017)Parameter Choice Matters: Validating Probe Parameters for Use in Mixed-Solvent Simulations., , and . Journal of Chemical Information and Modeling, 54 (8): 2190-2199 (2014)How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?, , , , and . WACV, page 1340-1349. IEEE Computer Society, (2018)pH-Dependent Transient Conformational States Control Optical Properties in Cyan Fluorescent Protein, , , and . Journal of the American Chemical Society, 137 (8): 2892-2900 (2015)PMID: 25647152.Multiple-objective Reinforcement Learning for Inverse Design and Identification., , and . CoRR, (2019)How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?, , , , and . CoRR, (2017)