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GPR

Gaussian Process Regression

Papers

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Showing 201–250 of 270 papers

TitleStatusHype
Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids—0
Stochastically forced ensemble dynamic mode decomposition for forecasting and analysis of near-periodic systems—0
Short-term prediction of photovoltaic power generation using Gaussian process regression—0
Lateral Force Prediction using Gaussian Process Regression for Intelligent Tire Systems—0
GPR-based Subsurface Object Detection and Reconstruction Using Random Motion and DepthNet—0
Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression—0
Understanding the effect of hyperparameter optimization on machine learning models for structure design problems—0
Gaussian Process Regression with Local Explanation—0
High Dimensional Bayesian Optimization Assisted by Principal Component AnalysisCode0
L1-GP: L1 Adaptive Control with Bayesian Learning—0
Autonomous Materials Discovery Driven by Gaussian Process Regression with Inhomogeneous Measurement Noise and Anisotropic Kernels—0
An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database—0
Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques—0
L_1-GP: L_1 Adaptive Control with Bayesian Learning—0
Defect segmentation: Mapping tunnel lining internal defects with ground penetrating radar data using a convolutional neural network—0
Predicting molecular dipole moments by combining atomic partial charges and atomic dipolesCode0
Analysis of Greenhouse Gases—0
Gaze-Sensing LEDs for Head Mounted Displays—0
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements—0
Projection based Active Gaussian Process Regression for Pareto Front Modeling—0
Approximate Inference for Fully Bayesian Gaussian Process RegressionCode0
Simulation of Turbulent Flow around a Generic High-Speed Train using Hybrid Models of RANS Numerical Method with Machine Learning—0
Tensor Basis Gaussian Process Models of Hyperelastic Materials—0
GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining—0
Domain-adaptive Crowd Counting via High-quality Image Translation and Density Reconstruction—0
Ultra-Reliable and Low-Latency Vehicular Communication: An Active Learning Approach—0
Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression—0
Scalable Gaussian Process Classification with Additive Noise for Various LikelihoodsCode0
Learning Enhanced Resolution-wise features for Human Pose Estimation—0
Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning—0
Modeling Daily Pan Evaporation in Humid Climates Using Gaussian Process Regression—0
An Improved Convolutional Neural Network System for Automatically Detecting Rebar in GPR Data—0
Gaussian Process Regression for Pricing Variable Annuities with Stochastic Volatility and Interest Rate—0
Bayesian Inference Gaussian Process Multiproxy Alignment of Continuous Signals (BIGMACS): Applications for PaleoceanographyCode0
Kernel Mode Decomposition and programmable/interpretable regression networksCode0
Applying Generative Adversarial Networks to Intelligent Subsurface Imaging and Identification—0
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection—0
A Bulirsch-Stoer algorithm using Gaussian processes—0
Machine Learning for Pricing American Options in High-Dimensional Markovian and non-Markovian models—0
Local Function Complexity for Active Learning via Mixture of Gaussian Processes—0
Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence—0
GPR-based Detection of Voids and Evaluation of Grouting Under Semi-rigid Basement—0
Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric DataCode0
Physics-Information-Aided Kriging: Constructing Covariance Functions using Stochastic Simulation Models—0
Deep Learning for Epidemiological Predictions—0
Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression—0
gprHOG and the popularity of Histogram of Oriented Gradients (HOG) for Buried Threat Detection in Ground-Penetrating Radar—0
Dictionary Learning for Adaptive GPR Landmine Classification—0
Learning Manifolds from Non-stationary Streaming Data—0
Fusion of hyperspectral and ground penetrating radar to estimate soil moistureCode0
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