Sustainability and Machine Learning Group
Sustainability and Machine Learning Group
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Blog posts
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation (Jun 2022)
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels (Dec 2021)
Publications
Scalable Interpolation of Satellite Altimetry Data with Probabilistic Machine Learning (2024)
Gaussian Processes on Cellular Complexes (2024)
Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems (2024)
Co-located OLCI Optical Imagery and SAR Altimetry from Sentinel-3 for Enhanced Arctic Spring Sea Ice Surface Classification (2024)
Scalable Data Assimilation with Message Passing (2024)
Actually Sparse Variational Gaussian Processes (2023)
Actually Sparse Variational Gaussian Processes (2022)
Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes (2022)
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation (2022)
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels (2021)
Seminar organization
Ollie Hamelijnck: Spatio-Temporal Variational Gaussian Processes (Mar 2022)
William Gregory: Improving Arctic Sea Ice Predictability with Gaussian Processes (Nov 2021)
Rachel Prudden: Stochastic Downscaling for Convective Regimes with Gaussian Random Fields (Sep 2021)
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