Deep Gaussian Processes with Gradients
Fuente:
arXiv
Guardado en:
| Autor principal: | Booth, Annie S. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Two-stage Design for Failure Probability Estimation with Gaussian Process Surrogates
por: Booth, Annie S., et al.
Publicado: (2024)
por: Booth, Annie S., et al.
Publicado: (2024)
Contour Location for Reliability in Airfoil Simulation Experiments using Deep Gaussian Processes
por: Booth, Annie S., et al.
Publicado: (2023)
por: Booth, Annie S., et al.
Publicado: (2023)
Nonstationary Gaussian Process Surrogates
por: Booth, Annie S., et al.
Publicado: (2023)
por: Booth, Annie S., et al.
Publicado: (2023)
Revisiting Penalized Likelihood Estimation for Gaussian Processes
por: Mutoh, Ayumi, et al.
Publicado: (2025)
por: Mutoh, Ayumi, et al.
Publicado: (2025)
Profile Bayesian Optimization for Expensive Computer Experiments
por: Kyger, Courtney, et al.
Publicado: (2025)
por: Kyger, Courtney, et al.
Publicado: (2025)
Bayesian Image-on-Image Regression via Deep Kernel Learning based Gaussian Processes
por: Ma, Guoxuan, et al.
Publicado: (2023)
por: Ma, Guoxuan, et al.
Publicado: (2023)
Actively Learning Joint Contours of Multiple Computer Experiments
por: Prim, Shih-Ni, et al.
Publicado: (2025)
por: Prim, Shih-Ni, et al.
Publicado: (2025)
Bayesian Bridge Gaussian Process Regression
por: Xu, Minshen, et al.
Publicado: (2025)
por: Xu, Minshen, et al.
Publicado: (2025)
Clustering the Nearest Neighbor Gaussian Process
por: Crisp, Ashlynn, et al.
Publicado: (2025)
por: Crisp, Ashlynn, et al.
Publicado: (2025)
Deep Gaussian Process Emulation with gradient Information and Sequential Design for Simulators with Sharp Variations
por: Yang, Yiming, et al.
Publicado: (2025)
por: Yang, Yiming, et al.
Publicado: (2025)
Inference for Log-Gaussian Cox Point Processes using Bayesian Deep Learning: Application to Human Oral Microbiome Image Data
por: Wang, Shuwan, et al.
Publicado: (2025)
por: Wang, Shuwan, et al.
Publicado: (2025)
Scalable Gaussian Process Inference with Stan
por: Hoffmann, Till, et al.
Publicado: (2023)
por: Hoffmann, Till, et al.
Publicado: (2023)
Gaussian Process with dissolution spline kernel
por: Murphy, Fiona, et al.
Publicado: (2024)
por: Murphy, Fiona, et al.
Publicado: (2024)
Log-Gaussian Cox Processes on General Metric Graphs
por: Bolin, David, et al.
Publicado: (2025)
por: Bolin, David, et al.
Publicado: (2025)
Gaussian Process Assisted Active Learning of Physical Laws
por: Chen, Jiuhai, et al.
Publicado: (2019)
por: Chen, Jiuhai, et al.
Publicado: (2019)
Synthesizing Epileptic Seizures: Gaussian Processes for EEG Generation
por: Moutonnet, Nina, et al.
Publicado: (2026)
por: Moutonnet, Nina, et al.
Publicado: (2026)
Block-Additive Gaussian Processes under Monotonicity Constraints
por: Deronzier, M., et al.
Publicado: (2024)
por: Deronzier, M., et al.
Publicado: (2024)
Energetic Variational Gaussian Process Regression for Computer Experiments
por: Kang, Lulu, et al.
Publicado: (2023)
por: Kang, Lulu, et al.
Publicado: (2023)
The Poisson-Gaussian Mixture Process: A Flexible and Robust Approach for Non-Gaussian Geostatistical Modeling
por: Gonçalves, F. B., et al.
Publicado: (2022)
por: Gonçalves, F. B., et al.
Publicado: (2022)
Deep Gaussian Process Emulation and Uncertainty Quantification for Large Computer Experiments
por: Yazdi, Faezeh, et al.
Publicado: (2024)
por: Yazdi, Faezeh, et al.
Publicado: (2024)
Modular Jump Gaussian Processes
por: Flowers, Anna R., et al.
Publicado: (2025)
por: Flowers, Anna R., et al.
Publicado: (2025)
Laplace Approximations for Mixed-Effects and Gaussian Process Quantile Regression
por: Nava, Andrea, et al.
Publicado: (2026)
por: Nava, Andrea, et al.
Publicado: (2026)
Credible Intervals for Probability of Failure with Gaussian Processes
por: Sorokin, Aleksei G., et al.
Publicado: (2023)
por: Sorokin, Aleksei G., et al.
Publicado: (2023)
Gaussian Process Boosting
por: Sigrist, Fabio
Publicado: (2020)
por: Sigrist, Fabio
Publicado: (2020)
Cumulative Treatment Effect Testing under Continuous Time Reinforcement Learning
por: Zhang, Jiuchen, et al.
Publicado: (2026)
por: Zhang, Jiuchen, et al.
Publicado: (2026)
Quantile Forecast Matching with a Bayesian Quantile Gaussian Process Model
por: Wadsworth, Spencer, et al.
Publicado: (2025)
por: Wadsworth, Spencer, et al.
Publicado: (2025)
Large-Scale Low-Rank Gaussian Process Prediction with Support Points
por: Song, Yan, et al.
Publicado: (2022)
por: Song, Yan, et al.
Publicado: (2022)
Bayesian Analysis of Sigmoidal Gaussian Cox Processes via Data Augmentation
por: Alie, Renaud, et al.
Publicado: (2022)
por: Alie, Renaud, et al.
Publicado: (2022)
Inference for Delay Differential Equations Using Manifold-Constrained Gaussian Processes
por: Zhao, Yuxuan, et al.
Publicado: (2024)
por: Zhao, Yuxuan, et al.
Publicado: (2024)
Fast Nonseparable Gaussian Stochastic Process with Application to Methylation Level Interpolation
por: Gu, Mengyang, et al.
Publicado: (2017)
por: Gu, Mengyang, et al.
Publicado: (2017)
Self-Supervised Learning with Gaussian Processes
por: Duan, Yunshan, et al.
Publicado: (2025)
por: Duan, Yunshan, et al.
Publicado: (2025)
Exchangeable Gaussian Processes with application to epidemics
por: Bouranis, Lampros, et al.
Publicado: (2025)
por: Bouranis, Lampros, et al.
Publicado: (2025)
Conditioning Gaussian Processes on Almost Anything
por: Moss, Henry, et al.
Publicado: (2026)
por: Moss, Henry, et al.
Publicado: (2026)
Gradient-based Active Learning with Gaussian Processes for Global Sensitivity Analysis
por: Lambert, Guerlain, et al.
Publicado: (2026)
por: Lambert, Guerlain, et al.
Publicado: (2026)
Gaussian Processes for Time Series with Lead-Lag Effects with applications to biology data
por: Mu, Wancen, et al.
Publicado: (2024)
por: Mu, Wancen, et al.
Publicado: (2024)
Copula-Based Time Series for Non-Gaussian and Non-Markovian Stationary Processes
por: Pappert, Sven, et al.
Publicado: (2026)
por: Pappert, Sven, et al.
Publicado: (2026)
The Bayesian Gaussian Process Latent Variable Model for Spatio-Temporal Stream Networks
por: Basson, Marno, et al.
Publicado: (2026)
por: Basson, Marno, et al.
Publicado: (2026)
Bayesian Inference of Spatially Varying Correlations via the Thresholded Correlation Gaussian Process
por: Li, Moyan, et al.
Publicado: (2024)
por: Li, Moyan, et al.
Publicado: (2024)
Bayesian Variable Selection via Hierarchical Gaussian Process Model in Computer Experiments
por: Yao, Xiao, et al.
Publicado: (2024)
por: Yao, Xiao, et al.
Publicado: (2024)
Wrapped Gaussian Process Functional Regression Model for Batch Data on Riemannian Manifolds
por: Liu, Jinzhao, et al.
Publicado: (2024)
por: Liu, Jinzhao, et al.
Publicado: (2024)
Ejemplares similares
-
Two-stage Design for Failure Probability Estimation with Gaussian Process Surrogates
por: Booth, Annie S., et al.
Publicado: (2024) -
Contour Location for Reliability in Airfoil Simulation Experiments using Deep Gaussian Processes
por: Booth, Annie S., et al.
Publicado: (2023) -
Nonstationary Gaussian Process Surrogates
por: Booth, Annie S., et al.
Publicado: (2023) -
Revisiting Penalized Likelihood Estimation for Gaussian Processes
por: Mutoh, Ayumi, et al.
Publicado: (2025) -
Profile Bayesian Optimization for Expensive Computer Experiments
por: Kyger, Courtney, et al.
Publicado: (2025)