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Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels
Nature
A majority of experimental disciplines face the challenge of exploring large and high-dimensional parameter spaces in search of new...
44 months ago
Metric Learning and Manifolds: Preserving the Intrinsic Geometry
Microsoft
In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction.
95 months ago
A survey on Bayesian nonparametric learning for time series analysis
Frontiers
Time series analysis aims to understand underlying patterns and relationships in data to inform decision-making. As time series data are becoming more...
6 months ago
Deep Bayesian Gaussian processes for uncertainty estimation in electronic health records
Nature
One major impediment to the wider use of deep learning for clinical decision making is the difficulty of assigning a level of confidence to...
32 months ago
Mechanical behavior predictions of additively manufactured microstructures using functional Gaussian process surrogates | npj Computational Materials
Nature
Relational linkages connecting process, structure, and properties are some of the most sought after goals in additive manufacturing (AM).
36 months ago
Use of Gaussian process regression for radiation mapping of a nuclear reactor with a mobile robot
Nature
Collection and interpolation of radiation observations is of vital importance to support routine operations in the nuclear sector globally,...
35 months ago
Stochastic learning and extremal-field map based autonomous guidance of low-thrust spacecraft
Nature
A supervised stochastic learning method called the Gaussian Process Regression (GPR) is used to design an autonomous guidance law for...
20 months ago
Uncertainty-aware mixed-variable machine learning for materials design
Nature
Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the...
19 months ago
Machine learning optimization for hybrid electric vehicle charging in renewable microgrids
Nature
Renewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources,...
2 weeks ago
nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes
Nature
Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of...
11 months ago