John Bradshaw - RankMe

26 papers A* 5B 1Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Challenging reaction prediction models to generalize to novel chemistry. CoRR John Bradshaw, Anji Zhang, Babak A. Mahjour, David E. Graff, Marwin H. S. Segler, Connor W. Coley
2024	J	`jnl`	Beyond Major Product Prediction: Reproducing Reaction Mechanisms with Machine Learning Models Trained on a Large-Scale Mechanistic Dataset. CoRR Joonyoung F. Joung, Mun Hong Fong, Jihye Roh, Zhengkai Tu, John Bradshaw, Connor W. Coley
2023	A*	`conf`	Prefix-Tree Decoding for Predicting Mass Spectra from Molecules. NeurIPS Samuel Goldman, John Bradshaw, Jiayi Xin, Connor W. Coley
2023	J	`jnl`	Prefix-tree Decoding for Predicting Mass Spectra from Molecules. CoRR Samuel Goldman, John Bradshaw, Jiayi Xin, Connor W. Coley
2022	A*	`conf`	Local Latent Space Bayesian Optimization over Structured Inputs. NeurIPS Natalie Maus, Haydn Thomas Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner
2022	J	`jnl`	Local Latent Space Bayesian Optimization over Structured Inputs. CoRR Natalie Maus, Haydn Thomas Jones, Juston S. Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner
2020	A*	`conf`	Barking up the right tree: an approach to search over molecule synthesis DAGs. NeurIPS John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2020	J	`jnl`	Barking up the right tree: an approach to search over molecule synthesis DAGs. CoRR John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	—	`conf`	A Generative Model For Electron Paths. ICLR (Poster) John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	A*	`conf`	A Model to Search for Synthesizable Molecules. NeurIPS John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	J	`jnl`	A Model to Search for Synthesizable Molecules. CoRR John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
2019	A*	`conf`	Are Generative Classifiers More Robust to Adversarial Attacks? ICML Yingzhen Li, John Bradshaw, Yash Sharma
2019	—	`conf`	Generating Molecules via Chemical Reactions. DGS@ICLR John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato
2018	J	`jnl`	Predicting Electron Paths. CoRR John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato
2011	J	`jnl`	Has the Picture Archiving and Communication System (PACS) Become a Commodity? J. Digit. Imaging James Chen, John Bradshaw, Paul G. Nagy
2009	J	`jnl`	A Machine Learning Approach to Weighting Schemes in the Data Fusion of Similarity Coefficients. J. Chem. Inf. Model. Jenny Chen, John D. Holliday, John Bradshaw
2003	J	`jnl`	Similarity Searching Using Reduced Graphs. J. Chem. Inf. Comput. Sci. Valerie J. Gillet, Peter Willett, John Bradshaw
2001	J	`jnl`	Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination. J. Chem. Inf. Comput. Sci. Gavin Harper, John Bradshaw, John C. Gittins, Darren V. S. Green, Andrew R. Leach
1999	B	`conf`	Computational analysis of molecular diversity for drug discovery. RECOMB Martin J. Bayley, Valerie J. Gillet, Peter Willett, John Bradshaw, Darren V. S. Green
1999	J	`jnl`	Implementation of a System for Reagent Selection and Library Enumeration, Profiling, and Design. J. Chem. Inf. Comput. Sci. Andrew R. Leach, John Bradshaw, Darren V. S. Green, Michael M. Hann, John J. Delany III
1999	J	`jnl`	Selecting Combinatorial Libraries to Optimize Diversity and Physical Properties. J. Chem. Inf. Comput. Sci. Valerie J. Gillet, Peter Willett, John Bradshaw, Darren V. S. Green
1998	J	`jnl`	Identification of Biological Activity Profiles Using Substructural Analysis and Genetic Algorithms. J. Chem. Inf. Comput. Sci. Valerie J. Gillet, Peter Willett, John Bradshaw
1998	J	`jnl`	Similarity and Dissimilarity Methods for Processing Chemical Structure Databases. Comput. J. Valerie J. Gillet, David J. Wild, Peter Willett, John Bradshaw
1997	J	`jnl`	The Effectiveness of Reactant Pools for Generating Structurally-Diverse Combinatorial Libraries. J. Chem. Inf. Comput. Sci. Valerie J. Gillet, Peter Willett, John Bradshaw
1995	J	`jnl`	The Application of Neural Networks in Conformational Analysis, 1. Prediction of Minimum and Maximum Interatomic Distances. J. Chem. Inf. Comput. Sci. Shaun N. Jordan, Andrew R. Leach, John Bradshaw
1993	J	`jnl`	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. Eleanor M. Ricketts, John Bradshaw, Mike Hann, Fiona Hayes, Neil Tanna, David M. Ricketts