Parameter Choice Matters: Validating Probe Parameters for Use in Mixed-Solvent Simulations. - Katrina W. Lexa; Garrett B. Goh; Heather A. Carlson (J. Chem. Inf. Model., 2014)

Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models. - Garrett B. Goh; Charles Siegel; Abhinav Vishnu; Nathan Oken Hodas; Nathan A. Baker (CoRR, 2017)

SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties. - Garrett B. Goh; Nathan O. Hodas; Charles Siegel; Abhinav Vishnu (CoRR, 2017)

ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction. - Garrett B. Goh; Charles Siegel; Abhinav Vishnu; Nathan O. Hodas (CoRR, 2017)

Deep learning for computational chemistry. - Garrett B. Goh; Nathan O. Hodas; Abhinav Vishnu (J. Comput. Chem., 2017)

IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks. - Khushmeen Sakloth; Wesley Beckner; Jim Pfaendtner; Garrett B. Goh (IEEE BigData, 2018)

Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction. - Garrett B. Goh; Charles Siegel; Abhinav Vishnu; Nathan Oken Hodas (KDD, 2018)

How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions? - Garrett B. Goh; Charles Siegel; Abhinav Vishnu; Nathan O. Hodas; Nathan A. Baker (WACV, 2018)

Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction. - Garrett B. Goh; Khushmeen Sakloth; Charles Siegel; Abhinav Vishnu; Jim Pfaendtner (CoRR, 2018)

Multiple-objective Reinforcement Learning for Inverse Design and Identification. - Haoran Wei; Mariefel Olarte; Garrett B. Goh (CoRR, 2019)

Explanatory Masks for Neural Network Interpretability. - Lawrence Phillips; Garrett B. Goh; Nathan O. Hodas (CoRR, 2019)