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10/09/2019
Multiple-objective Reinforcement Learning for Inverse Design and Identification
The aim of the inverse chemical design is to develop new molecules with ...
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09/13/2018
IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks
Deep neural networks (DNN) excel at extracting patterns. Through represe...
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08/13/2018
Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction
Deep learning algorithms excel at extracting patterns from raw data. Thr...
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12/07/2017
Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction
With access to large datasets, deep neural networks (DNN) have achieved ...
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12/07/2017
ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction
With access to large datasets, deep neural networks (DNN) have achieved ...
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12/06/2017
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
Chemical databases store information in text representations, and the SM...
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10/05/2017
How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?
In the last few years, we have seen the rise of deep learning applicatio...
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06/20/2017
Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models
In the last few years, we have seen the transformative impact of deep le...
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01/17/2017