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11/26/2022
Optimisation of a global climate model ensemble for prediction of extreme heat days
Adaptation-relevant predictions of climate change are often derived by c...
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10/29/2022
Ice Core Dating using Probabilistic Programming
Ice cores record crucial information about past climate. However, before...
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09/17/2019
Compositional uncertainty in deep Gaussian processes
Gaussian processes (GPs) are nonparametric priors over functions, and fi...
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07/10/2019
Interpretable Dynamics Models for Data-Efficient Reinforcement Learning
In this paper, we present a Bayesian view on model-based reinforcement l...
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06/26/2019
Modulated Bayesian Optimization using Latent Gaussian Process Models
We present an approach to Bayesian Optimization that allows for robust s...
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10/16/2018
Multimodal Deep Gaussian Processes
We propose a novel Bayesian approach to modelling multimodal data genera...
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10/08/2017
