John Bradshaw

According to our database, John Bradshaw authored at least 22 papers between 1993 and 2024.

Collaborative distances:

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

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

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

2022

Local Latent Space Bayesian Optimization over Structured Inputs.

Natalie Maus, Haydn T. Jones, Juston S. Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner

CoRR, 2022

Local Latent Space Bayesian Optimization over Structured Inputs.

Natalie Maus, Haydn Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner

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

2020

Barking up the right tree: an approach to search over molecule synthesis DAGs.

John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

A Model to Search for Synthesizable Molecules.

John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato

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

Are Generative Classifiers More Robust to Adversarial Attacks?

Yingzhen Li, John Bradshaw, Yash Sharma

Proceedings of the 36th International Conference on Machine Learning, 2019

Generating Molecules via Chemical Reactions.

John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

A Generative Model For Electron Paths.

John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Predicting Electron Paths.

John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato

CoRR, 2018

2011

Has the Picture Archiving and Communication System (PACS) Become a Commodity?

James Chen, John Bradshaw, Paul G. Nagy

J. Digit. Imaging, 2011

2009

A Machine Learning Approach to Weighting Schemes in the Data Fusion of Similarity Coefficients.

Jenny Chen, John D. Holliday, John Bradshaw

J. Chem. Inf. Model., 2009

2003

Similarity Searching Using Reduced Graphs.

Valerie J. Gillet, Peter Willett, John Bradshaw

J. Chem. Inf. Comput. Sci., 2003

2001

Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination.

Gavin Harper, John Bradshaw, John C. Gittins, Darren V. S. Green, Andrew R. Leach

J. Chem. Inf. Comput. Sci., 2001

1999

Implementation of a System for Reagent Selection and Library Enumeration, Profiling, and Design.

Andrew R. Leach, John Bradshaw, Darren V. S. Green, Michael M. Hann, John J. Delany III

J. Chem. Inf. Comput. Sci., 1999

Selecting Combinatorial Libraries to Optimize Diversity and Physical Properties.

Valerie J. Gillet, Peter Willett, John Bradshaw, Darren V. S. Green

J. Chem. Inf. Comput. Sci., 1999

Computational analysis of molecular diversity for drug discovery.

Martin J. Bayley, Valerie J. Gillet, Peter Willett, John Bradshaw, Darren V. S. Green

Proceedings of the Third Annual International Conference on Research in Computational Molecular Biology, 1999

1998

Identification of Biological Activity Profiles Using Substructural Analysis and Genetic Algorithms.

Valerie J. Gillet, Peter Willett, John Bradshaw

J. Chem. Inf. Comput. Sci., 1998

Similarity and Dissimilarity Methods for Processing Chemical Structure Databases.

Valerie J. Gillet, David J. Wild, Peter Willett, John Bradshaw

Comput. J., 1998

1997

The Effectiveness of Reactant Pools for Generating Structurally-Diverse Combinatorial Libraries.

Valerie J. Gillet, Peter Willett, John Bradshaw

J. Chem. Inf. Comput. Sci., 1997

1995

The Application of Neural Networks in Conformational Analysis, 1. Prediction of Minimum and Maximum Interatomic Distances.

Shaun N. Jordan, Andrew R. Leach, John Bradshaw

J. Chem. Inf. Comput. Sci., 1995

1993

Comparison of conformations of small molecule structures from the Protein Data Bank with those generated by Concord, Cobra, ChemDBS-3D, and Converter and those extracted from the Cambridge Structural Database.

Eleanor M. Ricketts, John Bradshaw, Mike Hann, Fiona Hayes, Neil Tanna, David M. Ricketts

J. Chem. Inf. Comput. Sci., 1993