130 citations · 327 across the 10 of their papers we have counts for
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cs.LG2023★ 1 cited
PDE-constrained Gaussian process surrogate modeling with uncertain data locations
Dongwei Ye, Weihao Yan, Christoph Brune +1
Gaussian process regression is widely applied in computational science and engineering for surrogate modeling owning to its kernel-based and probabilistic nature. In this work, we…
cs.LG2022★ 15 cited
Deep Kernel Learning of Dynamical Models from High-Dimensional Noisy Data
Nicolò Botteghi, Mengwu Guo, Christoph Brune
This work proposes a Stochastic Variational Deep Kernel Learning method for the data-driven discovery of low-dimensional dynamical models from high-dimensional noisy data. The fram…
cs.LG2021★ 3 cited
A brief note on understanding neural networks as Gaussian processes
Mengwu Guo
As a generalization of the work in [Lee et al., 2017], this note briefly discusses when the prior of a neural network output follows a Gaussian process, and how a neural-network-in…