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stat.ML2021
Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression
Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan
Deep Gaussian Processes (DGPs) are multi-layer, flexible extensions of Gaussian processes but their training remains challenging. Sparse approximations simplify the training but of…
stat.ML2018
Deep Gaussian Processes with Convolutional Kernels
Vinayak Kumar, Vaibhav Singh, P. K. Srijith +1
Deep Gaussian processes (DGPs) provide a Bayesian non-parametric alternative to standard parametric deep learning models. A DGP is formed by stacking multiple GPs resulting in a we…