Imagen de Portada

Review of Recent Advances in Gaussian Process Regression Methods

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lyu, Chenyi, Liu, Xingchi, Mihaylova, Lyudmila
Formato:	Preprint
Publicado:	2024
Materias:	Methodology Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Wireless Sensor Networks
por: Liu, Xingchi, et al.
Publicado: (2024)

Wasserstein-type Gaussian Process Regressions for Input Measurement Uncertainty
por: Luo, Hengrui, et al.
Publicado: (2026)

Advancing Counterfactual Inference through Nonlinear Quantile Regression
por: Xie, Shaoan, et al.
Publicado: (2023)

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models
por: Kündig, Pascal, et al.
Publicado: (2023)

Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting
por: Iong, Daniel, et al.
Publicado: (2024)

Determination of Particle-Size Distributions from Light-Scattering Measurement Using Constrained Gaussian Process Regression
por: Seyedheydari, Fahime, et al.
Publicado: (2025)

Modular Jump Gaussian Processes
por: Flowers, Anna R., et al.
Publicado: (2025)

Causal Inference with Latent Variables: Recent Advances and Future Prospectives
por: Zhu, Yaochen, et al.
Publicado: (2024)

Conditioning Gaussian Processes on Almost Anything
por: Moss, Henry, et al.
Publicado: (2026)

Self-Supervised Learning with Gaussian Processes
por: Duan, Yunshan, et al.
Publicado: (2025)

Distributional Off-Policy Evaluation with Deep Quantile Process Regression
por: Kuang, Qi, et al.
Publicado: (2026)

Gaussian Process Boosting
por: Sigrist, Fabio
Publicado: (2020)

Bayesian Causal Inference with Gaussian Process Networks
por: Giudice, Enrico, et al.
Publicado: (2024)

A Bayesian Take on Gaussian Process Networks
por: Giudice, Enrico, et al.
Publicado: (2023)

New Bounds for Sparse Variational Gaussian Processes
por: Titsias, Michalis K.
Publicado: (2025)

Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression
por: Song, Jiwoo, et al.
Publicado: (2024)

Aggregation Models with Optimal Weights for Distributed Gaussian Processes
por: Chen, Haoyuan, et al.
Publicado: (2024)

Diffusion-aware Censored Gaussian Processes for Demand Modelling
por: Rodrigues, Filipe
Publicado: (2025)

Overcoming Overfitting in Reinforcement Learning via Gaussian Process Diffusion Policy
por: Horprasert, Amornyos, et al.
Publicado: (2025)

Predicting Covariate-Driven Spatial Deformation for Nonstationary Gaussian Processes
por: Gu, Minghao, et al.
Publicado: (2026)

Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
por: Pion, Aurélien, et al.
Publicado: (2026)

A Dynamic, Ordinal Gaussian Process Item Response Theoretic Model
por: Chen, Yehu, et al.
Publicado: (2025)

The Kernel Manifold: A Geometric Approach to Gaussian Process Model Selection
por: Islam, Md Shafiqul, et al.
Publicado: (2026)

Transfer Learning of CATE with Kernel Ridge Regression
por: Kim, Seok-Jin, et al.
Publicado: (2025)

Robust and Conjugate Spatio-Temporal Gaussian Processes
por: Laplante, William, et al.
Publicado: (2025)

Predicting Electricity Consumption with Random Walks on Gaussian Processes
por: Hashimoto-Cullen, Chloé, et al.
Publicado: (2024)

Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes
por: Tan, Yu, et al.
Publicado: (2025)

Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes
por: Feng, Brandon R., et al.
Publicado: (2024)

Multi-Fidelity Quantile Regression
por: Liu, Yixiang, et al.
Publicado: (2026)

A Gaussian Process Model for Ordinal Data with Applications to Chemoinformatics
por: Gosnell, Arron, et al.
Publicado: (2024)

Exact Bayesian Gaussian Cox Processes Using Random Integral
por: Tang, Bingjing, et al.
Publicado: (2024)

AdapDISCOM: An Adaptive Sparse Regression Method for High-Dimensional Multimodal Data With Block-Wise Missingness and Measurement Errors
por: Baldé, Maimouna, et al.
Publicado: (2025)

Deep Fréchet Regression
por: Iao, Su I, et al.
Publicado: (2024)

Semiparametric Counterfactual Regression
por: Kim, Kwangho
Publicado: (2025)

Stagewise Boosting Distributional Regression
por: Wetscher, Mattias, et al.
Publicado: (2024)

Robust Tensor-on-Tensor Regression
por: Hirari, Mehdi, et al.
Publicado: (2026)

Bayesian Additive Distribution Regression
por: Linero, Antonio R., et al.
Publicado: (2026)

CP Degeneracy in Tensor Regression
por: Zhou, Ya, et al.
Publicado: (2020)

Generative Regression with IQ-BART
por: O'Hagan, Sean, et al.
Publicado: (2025)

Vector Quantile Regression on Manifolds
por: Pegoraro, Marco, et al.
Publicado: (2023)