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20232026
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math.ST2026

Convergence Rates for Learning Pseudo-Differential Operators

Jiaheng Chen, Daniel Sanz-Alonso

This paper establishes convergence rates for learning elliptic pseudo-differential operators, a fundamental operator class in partial differential equations and mathematical physic…

math.ST2025

On the Estimation of Gaussian Moment Tensors

Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso

This paper studies two estimators for Gaussian moment tensors: the standard sample moment estimator and a plug-in estimator based on Isserlis's theorem. We establish dimension-free…

math.ST2024

Precision and Cholesky Factor Estimation for Gaussian Processes

Jiaheng Chen, Daniel Sanz-Alonso

This paper studies the estimation of large precision matrices and Cholesky factors obtained by observing a Gaussian process at many locations. Under general assumptions on the prec…

math.ST2024

Optimal Estimation of Structured Covariance Operators

Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso +1

This paper establishes optimal convergence rates for estimation of structured covariance operators of Gaussian processes. We study banded operators with kernels that decay rapidly…

math.ST2023

Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters

Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso +1

This paper investigates covariance operator estimation via thresholding. For Gaussian random fields with approximately sparse covariance operators, we establish non-asymptotic boun…