Connor W. Coley

According to our database, Connor W. Coley authored at least 72 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

An algorithmic framework for synthetic cost-aware decision making in molecular design.

Jenna C. Fromer, Connor W. Coley

Nat. Comput. Sci., June, 2024

RDCanon: A Python Package for Canonicalizing the Order of Tokens in SMARTS Queries.

Babak A. Mahjour, Connor W. Coley

J. Chem. Inf. Model., 2024

MIST-CF: Chemical Formula Inference from Tandem Mass Spectra.

Samuel Goldman, Jiayi Xin, Joules Provenzano, Connor W. Coley

J. Chem. Inf. Model., 2024

OpenChemIE: An Information Extraction Toolkit for Chemistry Literature.

Vincent Fan, Yujie Qian, Alex Wang, Amber Wang, Connor W. Coley, Regina Barzilay

J. Chem. Inf. Model., 2024

Batched Bayesian optimization with correlated candidate uncertainties.

Jenna C. Fromer, Runzhong Wang, Mrunali Manjrekar, Austin Tripp, José Miguel Hernández-Lobato, Connor W. Coley

CoRR, 2024

Generative Artificial Intelligence for Navigating Synthesizable Chemical Space.

Wenhao Gao, Shitong Luo, Connor W. Coley

CoRR, 2024

Syntax-Guided Procedural Synthesis of Molecules.

Michael Sun, Alston Lo, Wenhao Gao, Minghao Guo, Veronika Thost, Jie Chen, Connor W. Coley, Wojciech Matusik

CoRR, 2024

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search.

Kevin Yu, Jihye Roh, Ziang Li, Wenhao Gao, Runzhong Wang, Connor W. Coley

CoRR, 2024

Beyond Major Product Prediction: Reproducing Reaction Mechanisms with Machine Learning Models Trained on a Large-Scale Mechanistic Dataset.

Joonyoung F. Joung, Mun Hong Fong, Jihye Roh, Zhengkai Tu, John Bradshaw, Connor W. Coley

CoRR, 2024

Substrate Scope Contrastive Learning: Repurposing Human Bias to Learn Atomic Representations.

Wenhao Gao, Priyanka Raghavan, Ron Shprints, Connor W. Coley

CoRR, 2024

Effective Protein-Protein Interaction Exploration with PPIretrieval.

Chenqing Hua, Connor W. Coley, Guy Wolf, Doina Precup, Shuangjia Zheng

CoRR, 2024

Projecting Molecules into Synthesizable Chemical Spaces.

Shitong Luo, Wenhao Gao, Zuofan Wu, Jian Peng, Connor W. Coley, Jianzhu Ma

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.

Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Neural scaling of deep chemical models.

Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally

Nat. Mac. Intell., October, 2023

Annotating metabolite mass spectra with domain-inspired chemical formula transformers.

Samuel Goldman, Jeremy Wohlwend, Martin Strazar, Guy Haroush, Ramnik J. Xavier, Connor W. Coley

Nat. Mac. Intell., September, 2023

RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing.

Yujie Qian, Jiang Guo, Zhengkai Tu, Connor W. Coley, Regina Barzilay

J. Chem. Inf. Model., July, 2023

Data Sharing in Chemistry: Lessons Learned and a Case for Mandating Structured Reaction Data.

Rocío Mercado, Steven M. Kearnes, Connor W. Coley

J. Chem. Inf. Model., July, 2023

MolScribe: Robust Molecular Structure Recognition with Image-to-Graph Generation.

Yujie Qian, Jiang Guo, Zhengkai Tu, Zhening Li, Connor W. Coley, Regina Barzilay

J. Chem. Inf. Model., April, 2023

Computer-aided multi-objective optimization in small molecule discovery.

Jenna C. Fromer, Connor W. Coley

Patterns, February, 2023

The promise and pitfalls of AI for molecular and materials synthesis.

Nicholas David, Wenhao Sun, Connor W. Coley

Nat. Comput. Sci., 2023

Scientific discovery in the age of artificial intelligence.

Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik

Nat., 2023

Pareto Optimization to Accelerate Multi-Objective Virtual Screening.

Jenna C. Fromer, David E. Graff, Connor W. Coley

CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.

Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

CoRR, 2023

Prefix-Tree Decoding for Predicting Mass Spectra from Molecules.

Samuel Goldman, John Bradshaw, Jiayi Xin, Connor W. Coley

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Equivariant Shape-Conditioned Generation of 3D Molecules for Ligand-Based Drug Design.

Keir Adams, Connor W. Coley

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Predictive Chemistry Augmented with Text Retrieval.

Yujie Qian, Zhening Li, Zhengkai Tu, Connor W. Coley, Regina Barzilay

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Machine learning modeling of family wide enzyme-substrate specificity screens.

Samuel Goldman, Ria Das, Kevin K. Yang, Connor W. Coley

PLoS Comput. Biol., 2022

pyscreener: A Python Wrapper for Computational Docking Software.

David E. Graff, Connor W. Coley

J. Open Source Softw., 2022

Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction Prediction.

Zhengkai Tu, Connor W. Coley

J. Chem. Inf. Model., 2022

Machine Learning on DNA-Encoded Library Count Data Using an Uncertainty-Aware Probabilistic Loss Function.

Katherine S. Lim, Andrew G. Reidenbach, Bruce K. Hua, Jeremy W. Mason, Christopher J. Gerry, Paul A. Clemons, Connor W. Coley

J. Chem. Inf. Model., 2022

Automated Chemical Reaction Extraction from Scientific Literature.

Jiang Guo, A. Santiago Ibanez-Lopez, Hanyu Gao, Victor Quach, Connor W. Coley, Klavs F. Jensen, Regina Barzilay

J. Chem. Inf. Model., 2022

Self-Focusing Virtual Screening with Active Design Space Pruning.

David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley

J. Chem. Inf. Model., 2022

Roughness of Molecular Property Landscapes and Its Impact on Modellability.

Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley

J. Chem. Inf. Model., 2022

Improving the performance of models for one-step retrosynthesis through re-ranking.

Min Htoo Lin, Zhengkai Tu, Connor W. Coley

J. Cheminformatics, 2022

De novo PROTAC design using graph-based deep generative models.

Divya Nori, Connor W. Coley, Rocío Mercado

CoRR, 2022

Robust Molecular Image Recognition: A Graph Generation Approach.

Yujie Qian, Zhengkai Tu, Jiang Guo, Connor W. Coley, Regina Barzilay

CoRR, 2022

A graph representation of molecular ensembles for polymer property prediction.

Matteo Aldeghi, Connor W. Coley

CoRR, 2022

Reinforced Genetic Algorithm for Structure-based Drug Design.

Tianfan Fu, Wenhao Gao, Connor W. Coley, Jimeng Sun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization.

Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor W. Coley

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design.

Wenhao Gao, Rocío Mercado, Connor W. Coley

Proceedings of the Tenth International Conference on Learning Representations, 2022

Differentiable Scaffolding Tree for Molecule Optimization.

Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations.

Keir Adams, Lagnajit Pattanaik, Connor W. Coley

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction Templates.

Esther Heid, Samuel Goldman, Karthik Sankaranarayanan, Connor W. Coley, Christoph Flamm, William H. Green Jr.

J. Chem. Inf. Model., 2021

Correction to Automated Chemical Reaction Extraction from Scientific Literature.

Jiang Guo, A. Santiago Ibanez-Lopez, Hanyu Gao, Victor Quach, Connor W. Coley, Klavs F. Jensen, Regina Barzilay

J. Chem. Inf. Model., 2021

Direct Optimization across Computer-Generated Reaction Networks Balances Materials Use and Feasibility of Synthesis Plans for Molecule Libraries.

Hanyu Gao, Jean Pauphilet, Thomas J. Struble, Connor W. Coley, Klavs F. Jensen

J. Chem. Inf. Model., 2021

Bringing Atomistic Deep Learning to Prime Time.

Nathan C. Frey, Siddharth Samsi, Bharath Ramsundar, Connor W. Coley, Vijay Gadepally

CoRR, 2021

Scalable Geometric Deep Learning on Molecular Graphs.

Nathan C. Frey, Siddharth Samsi, Joseph McDonald, Lin Li, Connor W. Coley, Vijay Gadepally

CoRR, 2021

Differentiable Scaffolding Tree for Molecular Optimization.

Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun

CoRR, 2021

BioNavi-NP: Biosynthesis Navigator for Natural Products.

Shuangjia Zheng, Tao Zeng, Chengtao Li, Binghong Chen, Connor W. Coley, Yuedong Yang, Ruibo Wu

CoRR, 2021

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics.

Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik

CoRR, 2021

Learning Graph Models for Retrosynthesis Prediction.

Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development.

Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles.

Octavian Ganea, Lagnajit Pattanaik, Connor W. Coley, Regina Barzilay, Klavs F. Jensen, William H. Green Jr., Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction.

Hangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang, Hongyu Guo

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Uncertainty Quantification Using Neural Networks for Molecular Property Prediction.

Lior Hirschfeld, Kyle Swanson, Kevin Yang, Regina Barzilay, Connor W. Coley

J. Chem. Inf. Model., 2020

The Synthesizability of Molecules Proposed by Generative Models.

Wenhao Gao, Connor W. Coley

J. Chem. Inf. Model., 2020

Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning.

Michael E. Fortunato, Connor W. Coley, Brian C. Barnes, Klavs F. Jensen

J. Chem. Inf. Model., 2020

Accelerating high-throughput virtual screening through molecular pool-based active learning.

David E. Graff, Eugene I. Shakhnovich, Connor W. Coley

CoRR, 2020

Message Passing Networks for Molecules with Tetrahedral Chirality.

Lagnajit Pattanaik, Octavian-Eugen Ganea, Ian Coley, Klavs F. Jensen, William H. Green Jr., Connor W. Coley

CoRR, 2020

Learning Graph Models for Template-Free Retrosynthesis.

Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay

CoRR, 2020

Autonomous discovery in the chemical sciences part II: Outlook.

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

CoRR, 2020

Autonomous discovery in the chemical sciences part I: Progress.

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

CoRR, 2020

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning.

Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Simon Blackburn, Karam M. J. Thomas, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Correction to Analyzing Learned Molecular Representations for Property Prediction.

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

J. Chem. Inf. Model., 2019

Analyzing Learned Molecular Representations for Property Prediction.

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

J. Chem. Inf. Model., 2019

RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application.

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

J. Chem. Inf. Model., 2019

Are Learned Molecular Representations Ready For Prime Time?

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

CoRR, 2019

Learning retrosynthetic planning through self-play.

John S. Schreck, Connor W. Coley, Kyle J. M. Bishop

CoRR, 2019

Retrosynthesis Prediction with Conditional Graph Logic Network.

Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

SCScore: Synthetic Complexity Learned from a Reaction Corpus.

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

J. Chem. Inf. Model., 2018

2017

Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.

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

J. Chem. Inf. Model., August, 2017

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network.

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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017