5 citations · 17 across the 7 of their papers we have counts for
8 papers
Multi-fidelity experimental design for ice-sheet simulation
Pierre Thodoroff, Markus Kaiser, Rosie Williams +5
Computer simulations are becoming an essential tool in many scientific fields from molecular dynamics to aeronautics. In glaciology, future predictions of sea level change require…
A locally time-invariant metric for climate model ensemble predictions of extreme risk
Mala Virdee, Markus Kaiser, Emily Shuckburgh +2
Adaptation-relevant predictions of climate change are often derived by combining climate model simulations in a multi-model ensemble. Model evaluation methods used in performance-b…
Ice Core Dating using Probabilistic Programming
Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite +5
Ice cores record crucial information about past climate. However, before ice core data can have scientific value, the chronology must be inferred by estimating the age as a functio…
Compositional uncertainty in deep Gaussian processes
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser +3
Gaussian processes (GPs) are nonparametric priors over functions. Fitting a GP implies computing a posterior distribution of functions consistent with the observed data. Similarly,…
Interpretable Dynamics Models for Data-Efficient Reinforcement Learning
Markus Kaiser, Clemens Otte, Thomas Runkler +1
In this paper, we present a Bayesian view on model-based reinforcement learning. We use expert knowledge to impose structure on the transition model and present an efficient learni…
Modulating Surrogates for Bayesian Optimization
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite +3
Bayesian optimization (BO) methods often rely on the assumption that the objective function is well-behaved, but in practice, this is seldom true for real-world objectives even if…