Methods › General › Non-Parametric Regression › Gaussian Process
Gaussian Process
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Gaussian Processes are non-parametric models for approximating functions. They rely upon a measure of similarity between points (the kernel function) to predict the value for an unseen point from training data. The models are fully probabilistic so uncertainty bounds are baked in with the model.
Image Source: Gaussian Processes for Machine Learning, C. E. Rasmussen & C. K. I. Williams
Papers archive 2025-07-28
30 shown of 2,473, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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A Risk-Aware Adaptive Robust MPC with Learned Uncertainty Quantification 15 Jul 2025 · 0 repositories · arXiv:2507.11420
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Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics 15 Jul 2025 · 1 repository · arXiv:2507.11240
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Active Learning for Manifold Gaussian Process Regression 26 Jun 2025 · 1 repository · arXiv:2506.20928
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Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics 26 Jun 2025 · 0 repositories · arXiv:2506.20935
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Trustworthy Prediction with Gaussian Process Knowledge Scores 23 Jun 2025 · 1 repository · arXiv:2506.18630
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Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction 20 Jun 2025 · 0 repositories · arXiv:2506.17036
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Digital twin for virtual sensing of ferry quays via a Gaussian Process Latent Force Model 17 Jun 2025 · 0 repositories · arXiv:2506.14925
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Single-Example Learning in a Mixture of GPDMs with Latent Geometries 17 Jun 2025 · 0 repositories · arXiv:2506.14563
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Bayesian Active Learning of (small) Quantile Sets through Expected Estimator Modification 16 Jun 2025 · 0 repositories · arXiv:2506.13211
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Overcoming Overfitting in Reinforcement Learning via Gaussian Process Diffusion Policy 16 Jun 2025 · 1 repository · arXiv:2506.13111
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Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes 15 Jun 2025 · 0 repositories · arXiv:2506.12701
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Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient? 13 Jun 2025 · 0 repositories · arXiv:2506.11831
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RoCA: Robust Cross-Domain End-to-End Autonomous Driving 11 Jun 2025 · 0 repositories · arXiv:2506.10145
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Data-Driven Nonlinear Regulation: Gaussian Process Learning 10 Jun 2025 · 0 repositories · arXiv:2506.09273
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Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment 10 Jun 2025 · 0 repositories · arXiv:2506.08719
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Not all those who drift are lost: Drift correction and calibration scheduling for the IoT 10 Jun 2025 · 0 repositories · arXiv:2506.09186
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Direct Integration of Recursive Gaussian Process Regression Into Extended Kalman Filters With Application to Vapor Compression Cycle Control 6 Jun 2025 · 0 repositories · arXiv:2506.06065
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Gaussian Process Diffeomorphic Statistical Shape Modelling Outperforms Angle-Based Methods for Assessment of Hip Dysplasia 5 Jun 2025 · 0 repositories · arXiv:2506.04886
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Nonlinear Sparse Bayesian Learning Methods with Application to Massive MIMO Channel Estimation with Hardware Impairments 4 Jun 2025 · 0 repositories · arXiv:2506.03775
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A Data-Based Architecture for Flight Test without Test Points 2 Jun 2025 · 0 repositories · arXiv:2506.02315
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Robust Satisficing Gaussian Process Bandits Under Adversarial Attacks 2 Jun 2025 · 0 repositories · arXiv:2506.01625
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Constrained Bayesian Optimization under Bivariate Gaussian Process with Application to Cure Process Optimization 30 May 2025 · 0 repositories · arXiv:2506.00174
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Quick-Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms 30 May 2025 · 0 repositories · arXiv:2505.24692
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Adaptive finite element type decomposition of Gaussian processes 29 May 2025 · 0 repositories · arXiv:2505.24066
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Fast Derivative Valuation from Volatility Surfaces using Machine Learning 29 May 2025 · 1 repository · arXiv:2505.22957
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Few-Shot Speech Deepfake Detection Adaptation with Gaussian Processes 29 May 2025 · 1 repository · arXiv:2505.23619
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A Multi-output Gaussian Process Regression with Negative Transfer Mitigation for Generating Boundary Test Scenarios of Multi-UAV Systems 28 May 2025 · 0 repositories · arXiv:2505.22331
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BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL 28 May 2025 · 0 repositories · arXiv:2505.21974
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Are Statistical Methods Obsolete in the Era of Deep Learning? 27 May 2025 · 0 repositories · arXiv:2505.21723
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A fast sound power prediction tool for genset noise using machine learning 26 May 2025 · 0 repositories · arXiv:2505.20079
Tasks archive 2025-07-28
20 shown of 486 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections