Papers

Learning Multimodal Graph-to-Graph Translation for Molecular Optimization (ICLR, 2019)

Wengong Jin, Kevin Yang, Regina Barzilay, and Tommi Jaakkola


A graph-convolutional neural network model for the prediction of chemical reactivity (Chemical Science, 2018)

Connor W. Coley, Wengong Jin, Luke Rogers, Timothy F. Jamison, Tommi S. Jaakkola, William H. Green, Regina Barzilay, and Klavs F. Jensen


Using Machine Learning To Predict Suitable Conditions for Organic Reactions (ACS Central Science, 2018)

Hanyu Gao, Thomas J. Struble, Connor W. Coley, Yuran Wang, William H. Green, and Klavs F. Jensen


Machine Learning in Computer-Aided Synthesis Planning (Accounts of Chemical Research, 2018)

Connor W. Coley, William H. Green, and Klavs F. Jensen


Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

Wengong Jin, Regina Barzilay, Tommi Jaakkola


SCScore: Synthetic Complexity Learned from a Reaction Corpus (Journal of Chemical Information and Modeling, 2018)

Connor W. Coley, Luke Rogers, William H. Green, and Klavs F. Jensen


Computer-Assisted Retrosynthesis Based on Molecular Similarity (ACS Central Science, 2017)

Connor W. Coley, Luke Rogers, William H. Green, and Klavs F. Jensen


Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network (NIPS 2017)

Wengong Jin, Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola


Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction (Journal of Chemical Information and Modeling, 2017)

Connor W. Coley, Regina Barzilay, William H. Green, Tommi S. Jaakkola, and Klavs F. Jensen


Prediction of Organic Reaction Outcomes Using Machine Learning (ACS, 2017)

Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola, William H. Green, and Klavs F. Jensen


Deriving Neural Architectures from Sequence and Graph Kernels (ICML, 2017)

Tao Lei, Wengong Jin, Regina Barzilay, and Tommi S. Jaakkola