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cs.LG2023★ 2 cited
Implicit Variational Inference for High-Dimensional Posteriors
Anshuk Uppal, Kristoffer Stensbo-Smidt, Wouter Boomsma +1
In variational inference, the benefits of Bayesian models rely on accurately capturing the true posterior distribution. We propose using neural samplers that specify implicit distr…
cs.LG2022
Adaptive Cholesky Gaussian Processes
Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz +3
We present a method to approximate Gaussian process regression models for large datasets by considering only a subset of the data. Our approach is novel in that the size of the sub…