1 citations · 2 across the 3 of their papers we have counts for
4 papers
gp2Scale: A Class of Compactly Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points
Marcus M. Noack, Mark D. Risser, Hengrui Luo +2
Despite a large corpus of recent work on scaling up Gaussian processes, a stubborn trade-off between computational speed, prediction and uncertainty quantification accuracy, and cu…
ASCRIBE-XR: Virtual Reality for Visualization of Scientific Imagery
Ronald J. Pandolfi, Jeffrey J. Donatelli, Julian Todd +1
ASCRIBE-XR, a novel computational platform designed to facilitate the visualization and exploration of 3D volumetric data and mesh data in the context of synchrotron experiments, i…
Ascribe New Dimensions to Scientific Data Visualization with VR
Daniela Ushizima, Guilherme Melo dos Santos, Zineb Sordo +2
For over half a century, the computer mouse has been the primary tool for interacting with digital data, yet it remains a limiting factor in exploring complex, multi-scale scientif…
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
Mark D. Risser, Marcus M. Noack, Hengrui Luo +1
The Gaussian process (GP) is a widely used probabilistic machine learning method with implicit uncertainty characterization for stochastic function approximation, stochastic modeli…