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GPR

Gaussian Process Regression

Papers

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Showing 76–100 of 270 papers

TitleStatusHype
Explainable Learning with Gaussian ProcessesCode0
A novel data generation scheme for surrogate modelling with deep operator networks—0
Data-Driven Stochastic AC-OPF using Gaussian ProcessesCode0
Gaussian-process-regression-based method for the localization of exceptional points in complex resonance spectra—0
Sparse discovery of differential equations based on multi-fidelity Gaussian process—0
Real-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach—0
Modeling Epidemic Spread: A Gaussian Process Regression ApproachCode0
Bayesian inversion of GPR waveforms for sub-surface material characterization: an uncertainty-aware retrieval of soil moisture and overlaying biomass properties—0
KF-PLS: Optimizing Kernel Partial Least-Squares (K-PLS) with Kernel Flows—0
On the variants of SVM methods applied to GPR data to classify tack coat characteristics in French pavements: two experimental case studies—0
Optimal Data Generation in Multi-Dimensional Parameter Spaces, using Bayesian Optimization—0
Novel models for fatigue life prediction under wideband random loads based on machine learning—0
A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-dimensional American Options—0
Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval—0
Guaranteed Coverage Prediction Intervals with Gaussian Process Regression—0
Enhanced Human-Robot Collaboration using Constrained Probabilistic Human-Motion Prediction—0
Comprehensive performance comparison among different types of features in data-driven battery state of health estimation—0
Learning-based Control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy—0
Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks—0
Bayesian tomography using polynomial chaos expansion and deep generative networks—0
Learning thermodynamically constrained equations of state with uncertaintyCode0
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing—0
A Depth-Adaptive Filtering Method for Effective GPR Tree Roots Detection in Tropical Area—0
A machine learning approach to the prediction of heat-transfer coefficients in micro-channels—0
Conditional variational autoencoder with Gaussian process regression recognition for parametric models—0
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