Publications

Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors  (ChemRxiv 2020)

Yanfei Guan, Connor W. Coley, Haoyang Wu, Duminda Ranasinghe, Esther Heid, Thomas J. Struble, Lagnajit Pattanaik, William H. Green and Klavs F. Jensen

Iterative experimental design based on active machine learning reduces the experimental burden associated with reaction screening (React. Chem. Eng. 2020)


Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning, (Chem. Sci. 2020)


Data augmentation and pretraining for template-based retrosynthetic prediction in computer-aided synthesis planning (J. Chem. Inf. Model. 2020, 60, 7, 3398–3407)

Michael E. Fortunato, Connor W. ColeyBrian C. Barnes, and Klavs F. Jensen

Current and future roles of artificial intelligence in medicinal chemistry synthesis (J. Med. Chem., J. Med. Chem. 2020, 63, 8667−8682)

Thomas J. StrubleJuan C. AlvarezScott P. BrownMilan ChytilJustin CisarRenee L. DesJarlaisOla EngkvistScott A. FrankDaniel R. GreveDaniel J. GriffinXinjun HouJeffrey W. JohannesConstantine KreatsoulasBrian LahueMiriam MatheaGeorg MogkChristos A. NicolaouAndrew D. PalmerDaniel J. PriceRichard I. RobinsonSebastian SalentinLi XingTommi JaakkolaWilliam. H. GreenRegina BarzilayConnor W. Coley and Klavs F. Jensen


Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list (React. Chem. Eng., 2020, 5, 367-376)


Generative Models for Graph-Based Protein Design (ICLR Workshop, 2019)

John Ingraham, Vikas Garg, Regina Barzilay, Tommi Jaakkola


Autonomous discovery in the chemical sciences part I: Progress (Angew. Chem. Int. Ed., 2020)

Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen


Autonomous discovery in the chemical sciences part II: Outlook (Angew. Chem. Int. Ed., 2020)

Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen


Multitask Prediction of Site Selectivity in Aromatic C-H Functionalization Reactions (React. Chem. Eng., 2020, 5, 896)

Thomas J. Struble, Connor W. Coley, Klavs F. Jensen


Path-Augmented Graph Transformer Network (arXiv preprint, 2019)

Benson Chen, Regina Barzilay, Tommi Jaakkola


Analyzing Learned Molecular Representations for Property Prediction (JCIM, 2019)

Kevin Yang, Kyle Swanson, Wengong Jin, Connor Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi Jaakkola, Klavs Jensen, Regina Barzilay


RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application (J. Chem. Inf. Model., 2019)

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


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

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


Self-Evolving Machine: A Continuously Improving Model for Molecular Thermochemistry (J. Phys. Chem. A, 2019)

Yi-Pei Li, Kehang Han, Colin A. Grambow, and William H. Green


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