2.4k citations · 12.3k across the 115 of their papers we have counts for
4 papers · 2 filters
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob R. Gardner, Geoff Pleiss, David Bindel +2
Despite advances in scalable models, the inference tools used for Gaussian processes (GPs) have yet to fully capitalize on developments in computing hardware. We present an efficie…
An empirical study on evaluation metrics of generative adversarial networks
Qiantong Xu, Gao Huang, Yang Yuan +4
Evaluating generative adversarial networks (GANs) is inherently challenging. In this paper, we revisit several representative sample-based evaluation metrics for GANs, and address…
Constant-Time Predictive Distributions for Gaussian Processes
Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger +1
One of the most compelling features of Gaussian process (GP) regression is its ability to provide well-calibrated posterior distributions. Recent advances in inducing point methods…
Product Kernel Interpolation for Scalable Gaussian Processes
Jacob R. Gardner, Geoff Pleiss, Ruihan Wu +2
Recent work shows that inference for Gaussian processes can be performed efficiently using iterative methods that rely only on matrix-vector multiplications (MVMs). Structured Kern…