Gareth John Conduit

17 papers Journal 17
YearRankTypeTitle / Venue / Authors
2026 J jnl
Comparing massively-multitask regression algorithms for drug discovery.
J. Comput. Aided Mol. Des.
Eric J. Martin, Xiang-wei Zhu, Patrick Riley, Steven Kearnes, Ekaterina A. Sosnina, Li Tian, Chi-Ming Che, Zijian Wang, Ying Wei, Thomas M. Whitehead, Gareth John Conduit, Matthew D. Segall
2026 J jnl
Talk Freely, Execute Strictly: Schema-Gated Agentic AI for Flexible and Reproducible Scientific Workflows.
CoRR
Joel Strickland, Arjun Vijeta, Chris Moores, Oliwia Bodek, Bogdan Nenchev, Thomas M. Whitehead, Charles Phillips, Karl Tassenberg, Gareth John Conduit, Ben Pellegrini
2024 J jnl
A compact yet flexible design space for large-scale nonperiodic 3D woven composites based on a weighted game for generating candidate tow architectures.
Comput. Aided Des.
Zhenpei Wang, Brian N. Cox, Shemuel Joash Kuehsamy, Mark Hyunpong Jhon, Olivier Sudre, N. Sridhar, Gareth John Conduit
2024 J jnl
Artificial intelligence (AI) futures: India-UK collaborations emerging from the 4th Royal Society Yusuf Hamied workshop.
Int. J. Inf. Manag.
Yogesh K. Dwivedi, Laurie Hughes, Harshad K. D. H. Bhadeshia, Sophia Ananiadou, Anthony G. Cohn, Jacqueline M. Cole, Gareth John Conduit, Maunendra Sankar Desarkar, Xinwei Wang
2024 J jnl
Modelling the nicotine pharmacokinetic profile for e-cigarettes using real time monitoring of consumers' physiological measurements and mouth level exposure.
BioData Min.
Krishna Prasad, Allen Griffiths, Kavya Agrawal, Michael McEwan, Flavio Macci, Marco Ghisoni, Matthew Stopher, Matthew Napleton, Joel Strickland, David Keating, Thomas M. Whitehead, Gareth John Conduit, Stacey Murray, Lauren Edward
2024 J jnl
Quantifying the Benefits of Imputation over QSAR Methods in Toxicology Data Modeling.
J. Chem. Inf. Model.
Thomas M. Whitehead, Joel Strickland, Gareth John Conduit, Alexandre Borrel, Daniel Mucs, Irene Baskerville-Abraham
2023 J jnl
Probabilistic selection and design of concrete using machine learning.
CoRR
Jessica C. Forsdyke, Bahdan Zviazhynski, Janet M. Lees, Gareth John Conduit
2023 J jnl
Unveil the unseen: Exploit information hidden in noise.
Appl. Intell.
Bahdan Zviazhynski, Gareth John Conduit
2022 J jnl
Unveil the unseen: Exploit information hidden in noise.
CoRR
Bahdan Zviazhynski, Gareth John Conduit
2021 J jnl
Imputation of sensory properties using deep learning.
J. Comput. Aided Mol. Des.
Samar Mahmoud, Benedict W. J. Irwin, Dmitriy Chekmarev, Shyam Vyas, Jeff Kattas, Thomas M. Whitehead, Tamsin Mansley, Jack Bikker, Gareth John Conduit, Matthew D. Segall
2020 J jnl
Machine learning to predict mesenchymal stem cell efficacy for cartilage repair.
PLoS Comput. Biol.
Yu Yang Fredrik Liu, Yin Lu, Steve Oh, Gareth John Conduit
2020 J jnl
Practical Applications of Deep Learning To Impute Heterogeneous Drug Discovery Data.
J. Chem. Inf. Model.
Benedict W. J. Irwin, Julian R. Levell, Thomas M. Whitehead, Matthew D. Segall, Gareth John Conduit
2020 J jnl
Predicting the state of charge and health of batteries using data-driven machine learning.
Nat. Mach. Intell.
Man-Fai Ng, Jin Zhao, Qingyu Yan, Gareth John Conduit, Zhi Wei Seh
2019 J jnl
Fragment Graphical Variational AutoEncoding for Screening Molecules with Small Data.
CoRR
John Armitage, Leszek J. Spalek, Malgorzata Nguyen, Mark Nikolka, Ian E. Jacobs, Lorena Marañón, Iyad Nasrallah, Guillaume Schweicher, Ivan Dimov, Dimitrios Simatos, Iain McCulloch, Christian B. Nielsen, Gareth John Conduit, Henning Sirringhaus
2019 J jnl
Imputation of Assay Bioactivity Data Using Deep Learning.
J. Chem. Inf. Model.
Thomas M. Whitehead, Benedict W. J. Irwin, Peter A. Hunt, Matthew D. Segall, Gareth John Conduit
2018 J jnl
Design of a nickel-base superalloy using a neural network.
CoRR
Bryce D. Conduit, Nick G. Jones, Howard J. Stone, Gareth John Conduit
2018 J jnl
Probabilistic design of a molybdenum-base alloy using a neural network.
CoRR
Bryce D. Conduit, Nick G. Jones, Howard J. Stone, Gareth John Conduit