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cs.LG2023
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…
cs.LG2023
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…