Low-rank computation of the posterior mean in Multi-Output Gaussian Processes
Fuente:
arXiv
Saved in:
| Main Authors: | Esche, Sebastian, Stoll, Martin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Preconditioned Additive Gaussian Processes with Fourier Acceleration
by: Wagner, Theresa, et al.
Published: (2025)
by: Wagner, Theresa, et al.
Published: (2025)
Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives
by: Wagner, Theresa, et al.
Published: (2024)
by: Wagner, Theresa, et al.
Published: (2024)
Efficient Differentiable Approximation of Generalized Low-rank Regularization
by: Li, Naiqi, et al.
Published: (2025)
by: Li, Naiqi, et al.
Published: (2025)
Guaranteed Sampling Flexibility for Low-tubal-rank Tensor Completion
by: Su, Bowen, et al.
Published: (2024)
by: Su, Bowen, et al.
Published: (2024)
Constructing Gaussian Processes via Samplets
by: Neugebauer, Marcel
Published: (2024)
by: Neugebauer, Marcel
Published: (2024)
Bayesian Quadrature: Gaussian Processes for Integration
by: Mahsereci, Maren, et al.
Published: (2026)
by: Mahsereci, Maren, et al.
Published: (2026)
Calibrated Computation-Aware Gaussian Processes
by: Hegde, Disha, et al.
Published: (2024)
by: Hegde, Disha, et al.
Published: (2024)
Low-rank adaptive physics-informed HyperDeepONets for solving differential equations
by: Zeudong, Etienne, et al.
Published: (2025)
by: Zeudong, Etienne, et al.
Published: (2025)
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
by: Blechschmidt, Jan, et al.
Published: (2025)
by: Blechschmidt, Jan, et al.
Published: (2025)
Sketching the Heat Kernel: Using Gaussian Processes to Embed Data
by: Gilbert, Anna C., et al.
Published: (2024)
by: Gilbert, Anna C., et al.
Published: (2024)
Mode-Shape Expansion Using Physics-Constrained Gaussian Process Regression
by: Ghahari, Farid
Published: (2026)
by: Ghahari, Farid
Published: (2026)
Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers
by: Pförtner, Marvin, et al.
Published: (2022)
by: Pförtner, Marvin, et al.
Published: (2022)
Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs
by: Sun, Shuwen, et al.
Published: (2025)
by: Sun, Shuwen, et al.
Published: (2025)
Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration
by: Kim, Hwanwoo, et al.
Published: (2024)
by: Kim, Hwanwoo, et al.
Published: (2024)
A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations
by: Mora, Carlos, et al.
Published: (2024)
by: Mora, Carlos, et al.
Published: (2024)
Christoffel-DPS: Optimal sensor placement in diffusion posterior sampling for arbitrary distributions
by: Rowbottom, James, et al.
Published: (2026)
by: Rowbottom, James, et al.
Published: (2026)
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
by: Chen, Yifan, et al.
Published: (2023)
by: Chen, Yifan, et al.
Published: (2023)
Posterior Covariance Structures in Gaussian Processes
by: Cai, Difeng, et al.
Published: (2024)
by: Cai, Difeng, et al.
Published: (2024)
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
by: Cohen, Jeremy E., et al.
Published: (2024)
by: Cohen, Jeremy E., et al.
Published: (2024)
A randomized algorithm to solve reduced rank operator regression
by: Turri, Giacomo, et al.
Published: (2023)
by: Turri, Giacomo, et al.
Published: (2023)
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations
by: Li, Zhaohui, et al.
Published: (2022)
by: Li, Zhaohui, et al.
Published: (2022)
LRTuckerRep: Low-rank Tucker Representation Model for Multi-dimensional Data Completion
by: Gong, Wenwu, et al.
Published: (2025)
by: Gong, Wenwu, et al.
Published: (2025)
Weighted quantization using MMD: From mean field to mean shift via gradient flows
by: Belhadji, Ayoub, et al.
Published: (2025)
by: Belhadji, Ayoub, et al.
Published: (2025)
$ε$-rank and the Staircase Phenomenon: New Insights into Neural Network Training Dynamics
by: Yang, Jiang, et al.
Published: (2024)
by: Yang, Jiang, et al.
Published: (2024)
A low-rank non-convex norm method for multiview graph clustering
by: Zahir, Alaeddine, et al.
Published: (2023)
by: Zahir, Alaeddine, et al.
Published: (2023)
Gaussian Process Regression under Computational and Epistemic Misspecification
by: Sanz-Alonso, Daniel, et al.
Published: (2023)
by: Sanz-Alonso, Daniel, et al.
Published: (2023)
Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation
by: Jonnalagadda, Bhavana, et al.
Published: (2024)
by: Jonnalagadda, Bhavana, et al.
Published: (2024)
A unified error analysis for randomized low-rank approximation with application to data assimilation
by: Di Perrotolo, Alexandre Scotto, et al.
Published: (2024)
by: Di Perrotolo, Alexandre Scotto, et al.
Published: (2024)
When big data actually are low-rank, or entrywise approximation of certain function-generated matrices
by: Budzinskiy, Stanislav
Published: (2024)
by: Budzinskiy, Stanislav
Published: (2024)
Slicing the Gaussian Mixture Wasserstein Distance
by: Piening, Moritz, et al.
Published: (2025)
by: Piening, Moritz, et al.
Published: (2025)
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
by: Berman, Jules, et al.
Published: (2024)
by: Berman, Jules, et al.
Published: (2024)
Overparameterization of deep ResNet: zero loss and mean-field analysis
by: Ding, Zhiyan, et al.
Published: (2021)
by: Ding, Zhiyan, et al.
Published: (2021)
Gaussian Processes and Reproducing Kernels: Connections and Equivalences
by: Kanagawa, Motonobu, et al.
Published: (2025)
by: Kanagawa, Motonobu, et al.
Published: (2025)
Regional climate projections using a deep-learning-based model-ranking and downscaling framework: Application to European climate zones
by: Loganathan, Parthiban, et al.
Published: (2025)
by: Loganathan, Parthiban, et al.
Published: (2025)
The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures
by: Adcock, Ben, et al.
Published: (2024)
by: Adcock, Ben, et al.
Published: (2024)
Neural Low-Discrepancy Sequences
by: Van Huffel, Michael Etienne, et al.
Published: (2025)
by: Van Huffel, Michael Etienne, et al.
Published: (2025)
Sparse discovery of differential equations based on multi-fidelity Gaussian process
by: Meng, Yuhuang, et al.
Published: (2024)
by: Meng, Yuhuang, et al.
Published: (2024)
Parametric model reduction of mean-field and stochastic systems via higher-order action matching
by: Berman, Jules, et al.
Published: (2024)
by: Berman, Jules, et al.
Published: (2024)
What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications
by: Williams, Emily, et al.
Published: (2024)
by: Williams, Emily, et al.
Published: (2024)
Stable Derivative Free Gaussian Mixture Variational Inference for Bayesian Inverse Problems
by: Che, Baojun, et al.
Published: (2025)
by: Che, Baojun, et al.
Published: (2025)
Similar Items
-
Preconditioned Additive Gaussian Processes with Fourier Acceleration
by: Wagner, Theresa, et al.
Published: (2025) -
Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives
by: Wagner, Theresa, et al.
Published: (2024) -
Efficient Differentiable Approximation of Generalized Low-rank Regularization
by: Li, Naiqi, et al.
Published: (2025) -
Guaranteed Sampling Flexibility for Low-tubal-rank Tensor Completion
by: Su, Bowen, et al.
Published: (2024) -
Constructing Gaussian Processes via Samplets
by: Neugebauer, Marcel
Published: (2024)