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publications
Gaussian Process Latent Variable Alignment Learning
Published in , 2019
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Modulating Surrogates for Bayesian Optimization
Published in , 2019
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Compositional uncertainty in deep Gaussian processes
Published in , 2020
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Monotonic Gaussian Process Flow
Published in , 2020
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Variational Bayesian approximation of inverse problems using sparse precision matrices
Published in , 2022
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Aligned Multi-Task Gaussian Process
Published in , 2022
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Multi-fidelity experimental design for ice-sheet simulation
Published in , 2022
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Probabilistic Machine Learning for Automated Ice Core Dating
Published in , 2022
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Ice Core Dating using Probabilistic Programming
Published in , 2022
Random Grid Neural Processes for Parametric Partial Differential Equations
Published in , 2023
A locally time-invariant metric for climate model ensemble predictions of extreme risk
Published in , 2023
Fully probabilistic deep models for forward and inverse problems in parametric PDEs
Published in , 2023
The Bayesian approach to inverse Robin problems
Published in , 2023
Variational Bayesian surrogate modelling with application to robust design optimisation
Published in , 2024
talks
Some Bayesian methods for inverse problems
Published:
teaching
ST445 Managing and Visualising Data
MSc course, LSE, Department of Statistics, 2024
View the course guide on the LSE website.
Visit the course website for additional details and resources.