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2020 – today
- 2024
[i6]Joonyoung F. Joung, Mun Hong Fong, Jihye Roh, Zhengkai Tu, John Bradshaw, Connor W. Coley:
Beyond Major Product Prediction: Reproducing Reaction Mechanisms with Machine Learning Models Trained on a Large-Scale Mechanistic Dataset. CoRR abs/2403.04580 (2024)- 2023
- [c8]Samuel Goldman, John Bradshaw, Jiayi Xin, Connor W. Coley:
Prefix-Tree Decoding for Predicting Mass Spectra from Molecules. NeurIPS 2023 - [i5]Samuel Goldman
, John Bradshaw, Jiayi Xin, Connor W. Coley:
Prefix-tree Decoding for Predicting Mass Spectra from Molecules. CoRR abs/2303.06470 (2023) - 2022
- [c7]Natalie Maus, Haydn Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner:
Local Latent Space Bayesian Optimization over Structured Inputs. NeurIPS 2022 - [i4]Natalie Maus, Haydn T. Jones, Juston S. Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner:
Local Latent Space Bayesian Optimization over Structured Inputs. CoRR abs/2201.11872 (2022) - 2020
- [c6]John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato:
Barking up the right tree: an approach to search over molecule synthesis DAGs. NeurIPS 2020 - [i3]John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato:
Barking up the right tree: an approach to search over molecule synthesis DAGs. CoRR abs/2012.11522 (2020)
2010 – 2019
- 2019
- [c5]John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato:
A Generative Model For Electron Paths. ICLR (Poster) 2019 - [c4]John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato:
Generating Molecules via Chemical Reactions. DGS@ICLR 2019 - [c3]Yingzhen Li, John Bradshaw, Yash Sharma:
Are Generative Classifiers More Robust to Adversarial Attacks? ICML 2019: 3804-3814 - [c2]John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato:
A Model to Search for Synthesizable Molecules. NeurIPS 2019: 7935-7947 - [i2]John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato:
A Model to Search for Synthesizable Molecules. CoRR abs/1906.05221 (2019) - 2018
- [i1]John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato:
Predicting Electron Paths. CoRR abs/1805.10970 (2018) - 2011
- [j11]James Chen, John Bradshaw, Paul G. Nagy:
Has the Picture Archiving and Communication System (PACS) Become a Commodity? J. Digit. Imaging 24(1): 6-10 (2011)
2000 – 2009
- 2009
- [j10]Jenny Chen, John D. Holliday, John Bradshaw:
A Machine Learning Approach to Weighting Schemes in the Data Fusion of Similarity Coefficients. J. Chem. Inf. Model. 49(2): 185-194 (2009) - 2003
- [j9]Valerie J. Gillet, Peter Willett, John Bradshaw:
Similarity Searching Using Reduced Graphs. J. Chem. Inf. Comput. Sci. 43(2): 338-345 (2003) - 2001
- [j8]Gavin Harper, John Bradshaw, John C. Gittins, Darren V. S. Green, Andrew R. Leach:
Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination. J. Chem. Inf. Comput. Sci. 41(5): 1295-1300 (2001)
1990 – 1999
- 1999
- [j7]Valerie J. Gillet, Peter Willett, John Bradshaw, Darren V. S. Green:
Selecting Combinatorial Libraries to Optimize Diversity and Physical Properties. J. Chem. Inf. Comput. Sci. 39(1): 169-177 (1999) - [j6]Andrew R. Leach, John Bradshaw, Darren V. S. Green, Michael M. Hann, John J. Delany III:
Implementation of a System for Reagent Selection and Library Enumeration, Profiling, and Design. J. Chem. Inf. Comput. Sci. 39(6): 1161-1172 (1999) - [c1]Martin J. Bayley, Valerie J. Gillet, Peter Willett, John Bradshaw, Darren V. S. Green:
Computational analysis of molecular diversity for drug discovery. RECOMB 1999: 321-330 - 1998
- [j5]Valerie J. Gillet, David J. Wild, Peter Willett, John Bradshaw:
Similarity and Dissimilarity Methods for Processing Chemical Structure Databases. Comput. J. 41(8): 547-558 (1998) - [j4]Valerie J. Gillet, Peter Willett, John Bradshaw:
Identification of Biological Activity Profiles Using Substructural Analysis and Genetic Algorithms. J. Chem. Inf. Comput. Sci. 38(2): 165-179 (1998) - 1997
- [j3]Valerie J. Gillet, Peter Willett, John Bradshaw:
The Effectiveness of Reactant Pools for Generating Structurally-Diverse Combinatorial Libraries. J. Chem. Inf. Comput. Sci. 37(4): 731-740 (1997) - 1995
- [j2]Shaun N. Jordan, Andrew R. Leach, John Bradshaw:
The Application of Neural Networks in Conformational Analysis, 1. Prediction of Minimum and Maximum Interatomic Distances. J. Chem. Inf. Comput. Sci. 35(3): 640-650 (1995) - 1993
- [j1]Eleanor M. Ricketts, John Bradshaw, Mike Hann, Fiona Hayes, Neil Tanna, David M. Ricketts:
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. J. Chem. Inf. Comput. Sci. 33(6): 905-925 (1993)
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