4 citations · 9 across the 11 of their papers we have counts for
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Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels
Matthias Bitzer, Mona Meister, Christoph Zimmer
Learning the kernel parameters for Gaussian processes is often the computational bottleneck in applications such as online learning, Bayesian optimization, or active learning. Amor…
Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems
Matthias Bitzer, Mona Meister, Christoph Zimmer
Learning precise surrogate models of complex computer simulations and physical machines often require long-lasting or expensive experiments. Furthermore, the modeled physical depen…
A posteriori error estimation for parabolic problems with dynamic boundary conditions
Robert Altmann, Christoph Zimmer
This paper is concerned with adaptive mesh refinement strategies for the spatial discretization of parabolic problems with dynamic boundary conditions. This includes the characteri…