Author

Matthias Katzfuss

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#machine learning Preprint Oct 2026

Derivative Gaussian Processes on a Two-Direction Budget

Gradient observations promise more accurate Gaussian process (GP) surrogates, but the cost of incorporating them has long stood in the way of realizing that promise. We propose a derivative GP with a budget of just two directions per observed gradient. One direction focuses on each gradient's direct contribution to tar...

Hyunseok Seung, Matthias Katzfuss · 0 citations

Preprint Aug 2026

Tensor Covariance Estimation via Kronecker-Structured Sparse Inverse Cholesky

A unified framework for scalable estimation of tensor covariances based on a Kronecker-structured sparse inverse Cholesky (KSIC) projection, proving that the KSIC estimator gainfully exploits cross-mode information and is robust to data scarcity.

Wentao Zhan, Matthias Katzfuss · 0 citations