Scholar
Andrew Millard
Google Scholar ID: u-i11fAAAAAJ
PhD Student, University of Liverpool
Sequential Monte Carlo Samplers
Bayesian Inference
Bayesian Deep Learning
Machine Learning
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Citations
1
H-index
1
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0
Publications
5
Co-authors
5
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Publications
9 items
Modelling Gas-Phase Reaction Kinetics with Guided Particle Diffusion Sampling
arXiv.org · 2026
Cited
0
Particle-Guided Diffusion for Gas-Phase Reaction Kinetics
2026
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0
Stop Preaching and Start Practising Data Frugality for Responsible Development of AI
2026
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0
Particle-Guided Diffusion Models for Partial Differential Equations
2026
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0
Investigating Batch Inference in a Sequential Monte Carlo Framework for Neural Networks
2026
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0
Hess-MC2: Sequential Monte Carlo Squared using Hessian Information and Second Order Proposals
2025
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0
Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles
2025
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0
Utilising Gradient-Based Proposals Within Sequential Monte Carlo Samplers for Training of Partial Bayesian Neural Networks
2025
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Resume (English only)
Co-authors
5 total
Joshua Murphy
University of Liverpool
Simon Maskell
University of Liverpool
Conor Rosato
University of Liverpool
Zheng Zhao
Assistant professor, Linköping University
Daniel Frisch
Karlsruher Institut für Technologie