Connor W. Coley

Orcid: 0000-0002-8271-8723

According to our database¹, Connor W. Coley authored at least 63 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2024

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

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

Effective Protein-Protein Interaction Exploration with PPIretrieval.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Neural scaling of deep chemical models.

[BibT_eX]

[DOI]

Rafael Gómez-Bombarelli

Connor W. Coley

Vijay Gadepally

Nat. Mac. Intell., October, 2023

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

[BibT_eX]

[DOI]

Nat. Mac. Intell., September, 2023

RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Rocío Mercado

Steven M. Kearnes

Connor W. Coley

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

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

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

Jenna C. Fromer

Connor W. Coley

Patterns, February, 2023

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

[BibT_eX]

[DOI]

Nicholas David

Wenhao Sun

Connor W. Coley

Nat. Comput. Sci., 2023

Scientific discovery in the age of artificial intelligence.

[BibT_eX]

[DOI]

Nat., 2023

Pareto Optimization to Accelerate Multi-Objective Virtual Screening.

[BibT_eX]

[DOI]

Jenna C. Fromer

David E. Graff

Connor W. Coley

CoRR, 2023

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Aria Mansouri Tehrani

Kamyar Azizzadenesheli

CoRR, 2023

Prefix-Tree Decoding for Predicting Mass Spectra from Molecules.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Keir Adams

Connor W. Coley

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Predictive Chemistry Augmented with Text Retrieval.

[BibT_eX]

[DOI]

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

2022

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

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2022

pyscreener: A Python Wrapper for Computational Docking Software.

[BibT_eX]

[DOI]

David E. Graff

Connor W. Coley

J. Open Source Softw., 2022

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2022

Automated Chemical Reaction Extraction from Scientific Literature.

[BibT_eX]

[DOI]

Jiang Guo

A. Santiago Ibanez-Lopez

J. Chem. Inf. Model., 2022

Self-Focusing Virtual Screening with Active Design Space Pruning.

[BibT_eX]

[DOI]

Edward O. Pyzer-Knapp

Connor W. Coley

J. Chem. Inf. Model., 2022

Roughness of Molecular Property Landscapes and Its Impact on Modellability.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Min Htoo Lin

Zhengkai Tu

Connor W. Coley

J. Cheminformatics, 2022

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

[BibT_eX]

[DOI]

Divya Nori

Connor W. Coley

Rocío Mercado

CoRR, 2022

Robust Molecular Image Recognition: A Graph Generation Approach.

[BibT_eX]

[DOI]

CoRR, 2022

A graph representation of molecular ensembles for polymer property prediction.

[BibT_eX]

[DOI]

Matteo Aldeghi

Connor W. Coley

CoRR, 2022

Reinforced Genetic Algorithm for Structure-based Drug Design.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Wenhao Gao

Rocío Mercado

Connor W. Coley

Proceedings of the Tenth International Conference on Learning Representations, 2022

Differentiable Scaffolding Tree for Molecule Optimization.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Jiang Guo

A. Santiago Ibanez-Lopez

J. Chem. Inf. Model., 2021

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

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2021

Bringing Atomistic Deep Learning to Prime Time.

[BibT_eX]

[DOI]

CoRR, 2021

Scalable Geometric Deep Learning on Molecular Graphs.

[BibT_eX]

[DOI]

CoRR, 2021

Differentiable Scaffolding Tree for Molecular Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

BioNavi-NP: Biosynthesis Navigator for Natural Products.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Learning Graph Models for Retrosynthesis Prediction.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2020

Uncertainty Quantification Using Neural Networks for Molecular Property Prediction.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

The Synthesizability of Molecules Proposed by Generative Models.

[BibT_eX]

[DOI]

Wenhao Gao

Connor W. Coley

J. Chem. Inf. Model., 2020

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

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

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

[BibT_eX]

[DOI]

David E. Graff

Eugene I. Shakhnovich

Connor W. Coley

CoRR, 2020

Message Passing Networks for Molecules with Tetrahedral Chirality.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Graph Models for Template-Free Retrosynthesis.

[BibT_eX]

[DOI]

CoRR, 2020

Autonomous discovery in the chemical sciences part II: Outlook.

[BibT_eX]

[DOI]

Connor W. Coley

Natalie S. Eyke

Klavs F. Jensen

CoRR, 2020

Autonomous discovery in the chemical sciences part I: Progress.

[BibT_eX]

[DOI]

Connor W. Coley

Natalie S. Eyke

Klavs F. Jensen

CoRR, 2020

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

[BibT_eX]

[DOI]

Sai Krishna Gottipati

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

2019

Correction to Analyzing Learned Molecular Representations for Property Prediction.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2019

Analyzing Learned Molecular Representations for Property Prediction.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2019

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

[BibT_eX]

[DOI]

Connor W. Coley

William H. Green Jr.

Klavs F. Jensen

J. Chem. Inf. Model., 2019

Are Learned Molecular Representations Ready For Prime Time?

[BibT_eX]

[DOI]

CoRR, 2019

Learning retrosynthetic planning through self-play.

[BibT_eX]

[DOI]

John S. Schreck

Connor W. Coley

Kyle J. M. Bishop

CoRR, 2019

Retrosynthesis Prediction with Conditional Graph Logic Network.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2018

2017

Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.

[BibT_eX]

[DOI]

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

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network.

[BibT_eX]

[DOI]

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

Connor W. Coley

Timeline

Legend:

Links

On csauthors.net:

Bibliography

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