Preconditioned Additive Gaussian Processes with Fourier Acceleration
Fuente:
arXiv
Guardado en:
| Autores principales: | Wagner, Theresa, Xu, Tianshi, Nestler, Franziska, Xi, Yuanzhe, Stoll, Martin |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives
por: Wagner, Theresa, et al.
Publicado: (2024)
por: Wagner, Theresa, et al.
Publicado: (2024)
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 Covariance Structures in Gaussian Processes
por: Cai, Difeng, et al.
Publicado: (2024)
por: Cai, Difeng, et al.
Publicado: (2024)
Fast and interpretable Support Vector Classification based on the truncated ANOVA decomposition
por: Akhalaya, Kseniya, et al.
Publicado: (2024)
por: Akhalaya, Kseniya, et al.
Publicado: (2024)
Preconditioning for Accelerated Gradient Descent Optimization and Regularization
por: Ye, Qiang
Publicado: (2024)
por: Ye, Qiang
Publicado: (2024)
Preconditioned FEM-based Neural Networks for Solving Incompressible Fluid Flows and Related Inverse Problems
por: Griese, Franziska, et al.
Publicado: (2024)
por: Griese, Franziska, et al.
Publicado: (2024)
Preconditioning for Physics-Informed Neural Networks
por: Liu, Songming, et al.
Publicado: (2024)
por: Liu, Songming, et al.
Publicado: (2024)
Multi-Preconditioned LBFGS for Training Finite-Basis PINNs
por: Salvadó-Benasco, Marc, et al.
Publicado: (2026)
por: Salvadó-Benasco, Marc, et al.
Publicado: (2026)
Fourier Neural Operators for Non-Markovian Processes:Approximation Theorems and Experiments
por: Lee, Wonjae, et al.
Publicado: (2025)
por: Lee, Wonjae, et al.
Publicado: (2025)
Constructing Gaussian Processes via Samplets
por: Neugebauer, Marcel
Publicado: (2024)
por: Neugebauer, Marcel
Publicado: (2024)
Bayesian Quadrature: Gaussian Processes for Integration
por: Mahsereci, Maren, et al.
Publicado: (2026)
por: Mahsereci, Maren, et al.
Publicado: (2026)
Calibrated Computation-Aware Gaussian Processes
por: Hegde, Disha, et al.
Publicado: (2024)
por: Hegde, Disha, et al.
Publicado: (2024)
Preconditioned Truncated Single-Sample Estimators for Scalable Stochastic Optimization
por: Xu, Tianshi, et al.
Publicado: (2025)
por: Xu, Tianshi, et al.
Publicado: (2025)
An Adaptive Factorized Nyström Preconditioner for Regularized Kernel Matrices
por: Zhao, Shifan, et al.
Publicado: (2023)
por: Zhao, Shifan, et al.
Publicado: (2023)
Preconditioned One-Step Generative Modeling for Bayesian Inverse Problems in Function Spaces
por: Cheng, Zilan, et al.
Publicado: (2026)
por: Cheng, Zilan, et al.
Publicado: (2026)
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
por: Blechschmidt, Jan, et al.
Publicado: (2025)
por: Blechschmidt, Jan, et al.
Publicado: (2025)
Designing Preconditioners for SGD: Local Conditioning, Noise Floors, and Basin Stability
por: Scott, Mitchell, et al.
Publicado: (2025)
por: Scott, Mitchell, et al.
Publicado: (2025)
Data-Parallel Neural Network Training via Nonlinearly Preconditioned Trust-Region Method
por: Alegría, Samuel A. Cruz, et al.
Publicado: (2025)
por: Alegría, Samuel A. Cruz, et al.
Publicado: (2025)
Windowed Fourier Propagator: A Frequency-Local Neural Operator for Wave Equations in Inhomogeneous Media
por: Cai, Yiyang, et al.
Publicado: (2026)
por: Cai, Yiyang, et al.
Publicado: (2026)
Sketching the Heat Kernel: Using Gaussian Processes to Embed Data
por: Gilbert, Anna C., et al.
Publicado: (2024)
por: Gilbert, Anna C., et al.
Publicado: (2024)
Towards Quantifying the Preconditioning Effect of Adam
por: Das, Rudrajit, et al.
Publicado: (2024)
por: Das, Rudrajit, et al.
Publicado: (2024)
Mode-Shape Expansion Using Physics-Constrained Gaussian Process Regression
por: Ghahari, Farid
Publicado: (2026)
por: Ghahari, Farid
Publicado: (2026)
Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers
por: Pförtner, Marvin, et al.
Publicado: (2022)
por: Pförtner, Marvin, et al.
Publicado: (2022)
Physics-embedded Fourier Neural Network for Partial Differential Equations
por: Xu, Qingsong, et al.
Publicado: (2024)
por: Xu, Qingsong, et al.
Publicado: (2024)
Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression
por: Yan, Mingsong, et al.
Publicado: (2026)
por: Yan, Mingsong, et al.
Publicado: (2026)
Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration
por: Kim, Hwanwoo, et al.
Publicado: (2024)
por: Kim, Hwanwoo, et al.
Publicado: (2024)
ANOVA-boosting for Random Fourier Features
por: Potts, Daniel, et al.
Publicado: (2024)
por: Potts, Daniel, et al.
Publicado: (2024)
A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations
por: Mora, Carlos, et al.
Publicado: (2024)
por: Mora, Carlos, et al.
Publicado: (2024)
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
por: Zhang, Fangzhao, et al.
Publicado: (2024)
por: Zhang, Fangzhao, et al.
Publicado: (2024)
High-Resolution Tensor-Network Fourier Methods for Exponentially Compressed Non-Gaussian Aggregate Distributions
por: Rodríguez-Aldavero, Juan José, et al.
Publicado: (2026)
por: Rodríguez-Aldavero, Juan José, et al.
Publicado: (2026)
Variational Matrix-Learning Fourier Networks for Parametric Multiphysics Surrogates
por: Li, Xinyu, et al.
Publicado: (2026)
por: Li, Xinyu, et al.
Publicado: (2026)
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
por: Li, Zongyi, et al.
Publicado: (2022)
por: Li, Zongyi, et al.
Publicado: (2022)
Component Fourier Neural Operator for Singularly Perturbed Differential Equations
por: Li, Ye, et al.
Publicado: (2024)
por: Li, Ye, et al.
Publicado: (2024)
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations
por: Li, Zhaohui, et al.
Publicado: (2022)
por: Li, Zhaohui, et al.
Publicado: (2022)
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
por: Lingsch, Levi, et al.
Publicado: (2023)
por: Lingsch, Levi, et al.
Publicado: (2023)
Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms
por: Hertrich, Johannes
Publicado: (2024)
por: Hertrich, Johannes
Publicado: (2024)
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators
por: Subedi, Unique, et al.
Publicado: (2024)
por: Subedi, Unique, et al.
Publicado: (2024)
What is a Sketch-and-Precondition Derivation for Low-Rank Approximation? Inverse Power Error or Inverse Power Estimation?
por: Xu, Ruihan, et al.
Publicado: (2025)
por: Xu, Ruihan, et al.
Publicado: (2025)
Learning High-dimensional Ionic Model Dynamics Using Fourier Neural Operators
por: Pellegrini, Luca, et al.
Publicado: (2025)
por: Pellegrini, Luca, et al.
Publicado: (2025)
Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws
por: Kim, Taeyoung, et al.
Publicado: (2024)
por: Kim, Taeyoung, et al.
Publicado: (2024)
Ejemplares similares
-
Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives
por: Wagner, Theresa, et al.
Publicado: (2024) -
Low-rank computation of the posterior mean in Multi-Output Gaussian Processes
por: Esche, Sebastian, et al.
Publicado: (2025) -
Posterior Covariance Structures in Gaussian Processes
por: Cai, Difeng, et al.
Publicado: (2024) -
Fast and interpretable Support Vector Classification based on the truncated ANOVA decomposition
por: Akhalaya, Kseniya, et al.
Publicado: (2024) -
Preconditioning for Accelerated Gradient Descent Optimization and Regularization
por: Ye, Qiang
Publicado: (2024)