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cs.LG2023
Sparse Variational Student-t Processes
Jian Xu, Delu Zeng
The theory of Bayesian learning incorporates the use of Student-t Processes to model heavy-tailed distributions and datasets with outliers. However, despite Student-t Processes hav…
cs.LG2023
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes
Jian Xu, Shian Du, Junmei Yang +2
Deep Gaussian Process (DGP) models offer a powerful nonparametric approach for Bayesian inference, but exact inference is typically intractable, motivating the use of various appro…