49 citations · 172 across the 25 of their papers we have counts for
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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★ 22 cited
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…