Garrett B. Goh | DeepAI

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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 ...

0 Haoran Wei, et al. ∙

∙ 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...

0 Khushmeen Sakloth, et al. ∙

∙ 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...

0 Garrett B. Goh, et al. ∙

∙ 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 ...

0 Garrett B. Goh, et al. ∙

∙ 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 ...

0 Garrett B. Goh, et al. ∙

∙ 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...

0 Garrett B. Goh, et al. ∙

∙ 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...

0 Garrett B. Goh, et al. ∙

∙ 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...

0 Garrett B. Goh, et al. ∙

∙ 01/17/2017

Deep Learning for Computational Chemistry

The rise and fall of artificial neural networks is well documented in th...

0 Garrett B. Goh, et al. ∙

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