Predictive posterior sampling from non-stationnary Gaussian process priors via Diffusion models with application to climate data
Fuente:
arXiv
Guardado en:
| Autores principales: | Cardoso, Gabriel V, Pereira, Mike |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Diffusion posterior sampling for simulation-based inference in tall data settings
por: Linhart, Julia, et al.
Publicado: (2024)
por: Linhart, Julia, et al.
Publicado: (2024)
Uncertainty quantification in model discovery by distilling interpretable material constitutive models from Gaussian process posteriors
por: Anton, David, et al.
Publicado: (2025)
por: Anton, David, et al.
Publicado: (2025)
A Gibbs posterior sampler for inverse problem based on prior diffusion model
por: Giovannelli, Jean-François
Publicado: (2026)
por: Giovannelli, Jean-François
Publicado: (2026)
Estimation of partially known Gaussian graphical models with score-based structural priors
por: Sevilla, Martín, et al.
Publicado: (2024)
por: Sevilla, Martín, et al.
Publicado: (2024)
Contraction rates for conjugate gradient and Lanczos approximate posteriors in Gaussian process regression
por: Stankewitz, Bernhard, et al.
Publicado: (2024)
por: Stankewitz, Bernhard, et al.
Publicado: (2024)
Dirichlet process mixtures of block $g$ priors for model selection and prediction in linear models
por: Porwal, Anupreet, et al.
Publicado: (2024)
por: Porwal, Anupreet, et al.
Publicado: (2024)
Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry
por: Tang, Pucheng, et al.
Publicado: (2025)
por: Tang, Pucheng, et al.
Publicado: (2025)
On learning functions over biological sequence space: relating Gaussian process priors, regularization, and gauge fixing
por: Petti, Samantha, et al.
Publicado: (2025)
por: Petti, Samantha, et al.
Publicado: (2025)
Scalable mixed-domain Gaussian process modeling and model reduction for longitudinal data
por: Timonen, Juho, et al.
Publicado: (2021)
por: Timonen, Juho, et al.
Publicado: (2021)
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators
por: Wang, Xinming, et al.
Publicado: (2024)
por: Wang, Xinming, et al.
Publicado: (2024)
Diffusion priors for Bayesian 3D reconstruction from incomplete measurements
por: Möbius, Julian L., et al.
Publicado: (2024)
por: Möbius, Julian L., et al.
Publicado: (2024)
Neural Koopman prior for data assimilation
por: Frion, Anthony, et al.
Publicado: (2023)
por: Frion, Anthony, et al.
Publicado: (2023)
Gaussian process surrogate model to approximate power grid simulators -- An application to the certification of a congestion management controller
por: Houdouin, Pierre, et al.
Publicado: (2025)
por: Houdouin, Pierre, et al.
Publicado: (2025)
Robust non-parametric mortality and fertility modelling and forecasting: Gaussian process regression approaches
por: Lam, Ka Kin, et al.
Publicado: (2021)
por: Lam, Ka Kin, et al.
Publicado: (2021)
Mitigating covariate shift in non-colocated data with learned parameter priors
por: Khan, Behraj, et al.
Publicado: (2024)
por: Khan, Behraj, et al.
Publicado: (2024)
Learning battery model parameter dynamics from data with recursive Gaussian process regression
por: Aitio, Antti, et al.
Publicado: (2023)
por: Aitio, Antti, et al.
Publicado: (2023)
Diffusion priors enhanced velocity model building from time-lag images using a neural operator
por: Ma, Xiao, et al.
Publicado: (2025)
por: Ma, Xiao, et al.
Publicado: (2025)
Gradient-enhanced deep Gaussian processes for multifidelity modelling
por: Bone, Viv, et al.
Publicado: (2024)
por: Bone, Viv, et al.
Publicado: (2024)
Training data membership inference via Gaussian process meta-modeling: a post-hoc analysis approach
por: Huang, Yongchao, et al.
Publicado: (2025)
por: Huang, Yongchao, et al.
Publicado: (2025)
Inference at the data's edge: Gaussian processes for modeling and inference under model-dependency, poor overlap, and extrapolation
por: Cho, Soonhong, et al.
Publicado: (2024)
por: Cho, Soonhong, et al.
Publicado: (2024)
Towards accurate extreme event likelihoods from diffusion model climate emulators
por: Manshausen, Peter, et al.
Publicado: (2026)
por: Manshausen, Peter, et al.
Publicado: (2026)
Expressive Mortality Models through Gaussian Process Kernels
por: Ludkovski, Mike, et al.
Publicado: (2023)
por: Ludkovski, Mike, et al.
Publicado: (2023)
Scalable Gaussian process modeling of parametrized spatio-temporal fields
por: Dama, Srinath, et al.
Publicado: (2026)
por: Dama, Srinath, et al.
Publicado: (2026)
MLPrE -- A tool for preprocessing and exploratory data analysis prior to machine learning model construction
por: Maxwell, David S, et al.
Publicado: (2025)
por: Maxwell, David S, et al.
Publicado: (2025)
Gaussian Process-based learning with new MCMC-based implementation of Wishart prior on correlation matrix
por: Warrior, Kane, et al.
Publicado: (2026)
por: Warrior, Kane, et al.
Publicado: (2026)
PDE-constrained Gaussian process surrogate modeling with uncertain data locations
por: Ye, Dongwei, et al.
Publicado: (2023)
por: Ye, Dongwei, et al.
Publicado: (2023)
Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models
por: Venkatraman, Siddarth, et al.
Publicado: (2025)
por: Venkatraman, Siddarth, et al.
Publicado: (2025)
Diffusion prior as a direct regularization term for FWI
por: Xie, Yuke, et al.
Publicado: (2025)
por: Xie, Yuke, et al.
Publicado: (2025)
Surrogate modeling for Bayesian optimization beyond a single Gaussian process
por: Lu, Qin, et al.
Publicado: (2022)
por: Lu, Qin, et al.
Publicado: (2022)
Robust and Differentially Private PCA for non-Gaussian data
por: Kim, Minwoo, et al.
Publicado: (2025)
por: Kim, Minwoo, et al.
Publicado: (2025)
Variational Autoencoder for Generating Broader-Spectrum prior Proposals in Markov chain Monte Carlo Methods
por: Borges, Marcio, et al.
Publicado: (2025)
por: Borges, Marcio, et al.
Publicado: (2025)
Expert-elicitation method for non-parametric joint priors using normalizing flows
por: Bockting, Florence, et al.
Publicado: (2024)
por: Bockting, Florence, et al.
Publicado: (2024)
Using ARIMA to Predict the Expansion of Subscriber Data Consumption
por: Nkongolo, Mike Wa
Publicado: (2024)
por: Nkongolo, Mike Wa
Publicado: (2024)
Rolled Gaussian process models for curves on manifolds
por: Preston, Simon, et al.
Publicado: (2025)
por: Preston, Simon, et al.
Publicado: (2025)
Student-t processes as infinite-width limits of posterior Bayesian neural networks
por: Caporali, Francesco, et al.
Publicado: (2025)
por: Caporali, Francesco, et al.
Publicado: (2025)
Tukey g-and-h neural network regression for non-Gaussian data
por: Guillaumin, Arthur P., et al.
Publicado: (2024)
por: Guillaumin, Arthur P., et al.
Publicado: (2024)
PAC-Bayesian risk bounds for fully connected deep neural network with Gaussian priors
por: Mai, The Tien
Publicado: (2025)
por: Mai, The Tien
Publicado: (2025)
Composing diffusion priors with explicit physical context via generative Gibbs sampling
por: Wang, Weizhou, et al.
Publicado: (2026)
por: Wang, Weizhou, et al.
Publicado: (2026)
Low-rank computation of the posterior mean in Multi-Output Gaussian Processes
por: Esche, Sebastian, et al.
Publicado: (2025)
por: Esche, Sebastian, et al.
Publicado: (2025)
Posterior sampling via Langevin dynamics based on generative priors
por: Purohit, Vishal, et al.
Publicado: (2024)
por: Purohit, Vishal, et al.
Publicado: (2024)
Ejemplares similares
-
Diffusion posterior sampling for simulation-based inference in tall data settings
por: Linhart, Julia, et al.
Publicado: (2024) -
Uncertainty quantification in model discovery by distilling interpretable material constitutive models from Gaussian process posteriors
por: Anton, David, et al.
Publicado: (2025) -
A Gibbs posterior sampler for inverse problem based on prior diffusion model
por: Giovannelli, Jean-François
Publicado: (2026) -
Estimation of partially known Gaussian graphical models with score-based structural priors
por: Sevilla, Martín, et al.
Publicado: (2024) -
Contraction rates for conjugate gradient and Lanczos approximate posteriors in Gaussian process regression
por: Stankewitz, Bernhard, et al.
Publicado: (2024)