{"total":38,"rows":[{"id":"2305.04933","title":"Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial","created":"2023-05-07","cited_by_count":27,"area":null},{"id":"2110.08323","title":"On Learning the Transformer Kernel","created":"2021-10-15","cited_by_count":15,"area":null},{"id":"2407.00809","title":"Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning","created":"2024-06-30","cited_by_count":11,"area":null},{"id":"2106.10773","title":"Neural Spectral Marked Point Processes","created":"2021-06-20","cited_by_count":10,"area":null},{"id":"2205.09070","title":"Exact Gaussian Processes for Massive Datasets via Non-Stationary Sparsity-Discovering Kernels","created":"2022-05-18","cited_by_count":9,"area":null},{"id":"2107.10066","title":"Adaptive Inducing Points Selection For Gaussian Processes","created":"2021-07-21","cited_by_count":8,"area":null},{"id":"2202.09233","title":"Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures","created":"2022-02-18","cited_by_count":8,"area":null},{"id":"2109.10898","title":"A Robust Asymmetric Kernel Function for Bayesian Optimization, with Application to Image Defect Detection in Manufacturing Systems","created":"2021-09-22","cited_by_count":6,"area":null},{"id":"2103.10134","title":"Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey","created":"2021-03-18","cited_by_count":5,"area":null},{"id":"2102.12792","title":"Mixed Variable Bayesian Optimization with Frequency Modulated Kernels","created":"2021-02-25","cited_by_count":4,"area":null},{"id":"2106.07452","title":"Marginalising over Stationary Kernels with Bayesian Quadrature","created":"2021-06-14","cited_by_count":4,"area":null},{"id":"2212.01503","title":"Online Estimation of the Koopman Operator Using Fourier Features","created":"2022-12-03","cited_by_count":4,"area":null},{"id":"2303.10022","title":"Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems","created":"2023-03-17","cited_by_count":4,"area":null},{"id":"2103.06950","title":"The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain","created":"2021-03-11","cited_by_count":3,"area":null},{"id":"2103.15213","title":"A Temporal Kernel Approach for Deep Learning with Continuous-time Information","created":"2021-03-28","cited_by_count":3,"area":null},{"id":"2105.04538","title":"Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels","created":"2021-05-10","cited_by_count":2,"area":null},{"id":"2109.12111","title":"Accurate Remaining Useful Life Prediction with Uncertainty Quantification: a Deep Learning and Nonstationary Gaussian Process Approach","created":"2021-09-23","cited_by_count":2,"area":null},{"id":"2208.09978","title":"Bayesian Complementary Kernelized Learning for Multidimensional Spatiotemporal Data","created":"2022-08-21","cited_by_count":2,"area":null},{"id":"2210.10964","title":"Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning","created":"2022-10-20","cited_by_count":2,"area":null},{"id":"2210.12363","title":"Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior","created":"2022-10-22","cited_by_count":2,"area":null},{"id":"2310.17023","title":"On the Identifiability and Interpretability of Gaussian Process Models","created":"2023-10-25","cited_by_count":2,"area":null},{"id":"2410.03581","title":"Nonstationary Sparse Spectral Permanental Process","created":"2024-10-04","cited_by_count":2,"area":null},{"id":"2602.00987","title":"Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees","created":"2026-02-01","cited_by_count":2,"area":null},{"id":"2502.08253","title":"Multi-View Oriented GPLVM: Expressiveness and Efficiency","created":"2025-02-12","cited_by_count":1,"area":null},{"id":"2505.09026","title":"Probabilistic Wind Power Modelling via Heteroscedastic Non-Stationary Gaussian Processes","created":"2025-05-13","cited_by_count":1,"area":null},{"id":"2505.21658","title":"STACI: Spatio-Temporal Aleatoric Conformal Inference","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2506.16316","title":"Bayesian Optimization over Bounded Domains with the Beta Product Kernel","created":"2025-06-19","cited_by_count":1,"area":null},{"id":"2106.00719","title":"Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network","created":"2021-06-01","cited_by_count":0,"area":null},{"id":"2107.12797","title":"Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference","created":"2021-07-26","cited_by_count":0,"area":null},{"id":"2109.11579","title":"Remaining useful life prediction with uncertainty quantification: development of a highly accurate model for rotating machinery","created":"2021-09-23","cited_by_count":0,"area":null},{"id":"2404.12478","title":"A New Reliable & Parsimonious Learning Strategy Comprising Two Layers of Gaussian Processes, to Address Inhomogeneous Empirical Correlation Structures","created":"2024-04-18","cited_by_count":0,"area":null},{"id":"2406.00438","title":"Stein Random Feature Regression","created":"2024-06-01","cited_by_count":0,"area":null},{"id":"2505.18526","title":"Scalable Deep Basis Kernel Gaussian Processes","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2602.23006","title":"Regular Fourier Features for Nonstationary Gaussian Processes","created":"2026-02-26","cited_by_count":0,"area":null},{"id":"2606.11255","title":"Bernstein-Schur Kernels: Random Features by Sketched Modulation and Radial Randomization","created":"2026-06-08","cited_by_count":0,"area":null},{"id":"2607.10793","title":"Hierarchical Bayesian Quadrature","created":"2026-07-12","cited_by_count":0,"area":null},{"id":"2607.18282","title":"ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization","created":"2026-06-30","cited_by_count":0,"area":null},{"id":"2608.26974","title":"Why not to use the Gaussian kernel","created":"2026-08-27","cited_by_count":0,"area":null}],"next_cursor":null}