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Kristoffer Stensbo-Smidt

2 accepted papers

2023

Adaptive Cholesky Gaussian Processes

AISTATS 2023poster

We present a method to approximate Gaussian process regression models to large datasets by considering only a subset of the data. Our approach is novel in that the size of the subset is selected on the fly during exact inference with little computational overhead. From an empirical observation that…

2023

Implicit Variational Inference for High-Dimensional Posteriors

NeurIPS 2023spotlight

In variational inference, the benefits of Bayesian models rely on accurately capturing the true posterior distribution. We propose using neural samplers that specify implicit distributions, which are well-suited for approximating complex multimodal and correlated posteriors in high-dimensional space…