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GPR

Gaussian Process Regression

Papers

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Showing 151–175 of 270 papers

TitleStatusHype
MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation—0
Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks—0
Neural network with optimal neuron activation functions based on additive Gaussian process regression—0
Normative Modeling using Multimodal Variational Autoencoders to Identify Abnormal Brain Structural Patterns in Alzheimer Disease—0
Novel models for fatigue life prediction under wideband random loads based on machine learning—0
On Choosing Training and Testing Data for Supervised Algorithms in Ground Penetrating Radar Data for Buried Threat Detection—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
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection—0
Overlapping Cover Local Regression Machines—0
Over-the-Air Gaussian Process Regression Based on Product of Experts—0
PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations—0
Personality Traits and Job Candidate Screening via Analyzing Facial Videos—0
Photoelectric Factor Prediction Using Automated Learning and Uncertainty Quantification—0
Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence—0
Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids—0
Physics-Information-Aided Kriging: Constructing Covariance Functions using Stochastic Simulation Models—0
PIQI: Perceptual Image Quality Index based on Ensemble of Gaussian Process Regression—0
Plant species richness prediction from DESIS hyperspectral data: A comparison study on feature extraction procedures and regression models—0
Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders—0
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing—0
Predicting Stock Market Crash with Bayesian Generalised Pareto Regression—0
Projection based Active Gaussian Process Regression for Pareto Front Modeling—0
Quantification of Damage Using Indirect Structural Health Monitoring—0
Quantum assisted Gaussian process regression—0
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