55 citations · 118 across the 12 of their papers we have counts for
3 papers · 1 filter
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
Geoff Pleiss, John P. Cunningham
Large width limits have been a recent focus of deep learning research: modulo computational practicalities, do wider networks outperform narrower ones? Answering this question has…
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations
Luhuan Wu, Andrew Miller, Lauren Anderson +3
We examine the general problem of inter-domain Gaussian Processes (GPs): problems where the GP realization and the noisy observations of that realization lie on different domains.…
Bias-Free Scalable Gaussian Processes via Randomized Truncations
Andres Potapczynski, Luhuan Wu, Dan Biderman +2
Scalable Gaussian Process methods are computationally attractive, yet introduce modeling biases that require rigorous study. This paper analyzes two common techniques: early trunca…