Matthias Katzfuss

According to our database, Matthias Katzfuss authored at least 16 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference.

Myeongjong Kang, Matthias Katzfuss

Stat. Comput., June, 2023

Sparse Cholesky factorization by greedy conditional selection.

Stephen Huan, Joseph Guinness, Matthias Katzfuss, Houman Owhadi, Florian Schäfer

CoRR, 2023

Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks.

Felix Jimenez, Matthias Katzfuss

CoRR, 2023

Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization.

Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Schäfer, Matthias Katzfuss

CoRR, 2023

Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization.

Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Tobias Schaefer, Matthias Katzfuss

Proceedings of the International Conference on Machine Learning, 2023

Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes.

Felix Jimenez, Matthias Katzfuss

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering.

Marcin Jurek, Matthias Katzfuss

Stat. Comput., 2022

Spatial Surface Reflectance Retrievals for Visible/Shortwave Infrared Remote Sensing via Gaussian Process Priors.

Daniel Zilber, David R. Thompson, Matthias Katzfuss, Vijay Natraj, Jonathan Hobbs, Amy Braverman

Remote. Sens., 2022

Scaled Vecchia Approximation for Fast Computer-Model Emulation.

Matthias Katzfuss, Joseph Guinness, Earl Lawrence

SIAM/ASA J. Uncertain. Quantification, 2022

Scalable Gaussian-process regression and variable selection using Vecchia approximations.

Jian Cao, Joseph Guinness, Marc G. Genton, Matthias Katzfuss

J. Mach. Learn. Res., 2022

2021

Sparse Cholesky Factorization by Kullback-Leibler Minimization.

Florian Schäfer, Matthias Katzfuss, Houman Owhadi

SIAM J. Sci. Comput., 2021

Spatial Retrievals of Atmospheric Carbon Dioxide from Satellite Observations.

Jonathan Hobbs, Matthias Katzfuss, Daniel Zilber, Jenný Brynjarsdóttir, Anirban Mondal, Veronica J. Berrocal

Remote. Sens., 2021

Multi-Resolution Filters for Massive Spatio-Temporal Data.

Marcin Jurek, Matthias Katzfuss

J. Comput. Graph. Stat., 2021

Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data.

Daniel Zilber, Matthias Katzfuss

Comput. Stat. Data Anal., 2021

2017

Parallel inference for massive distributed spatial data using low-rank models.

Matthias Katzfuss, Dorit Hammerling

Stat. Comput., 2017

2014

Spatio-Temporal Data Fusion for Very Large Remote Sensing Datasets.

Hai Nguyen, Matthias Katzfuss, Noel Cressie, Amy Braverman

Technometrics, 2014