Matthias Katzfuss

23 papers A* 1A 2Journal 20

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fast Gaussian Process Approximations for Autocorrelated Data. CoRR Ahmadreza Chokhachian, Matthias Katzfuss, Yu Ding
2025	J	`jnl`	Nonstationary Spatial Modeling of Massive Global Satellite Data. J. Comput. Graph. Stat. Huang Huang, Lewis R. Blake, Matthias Katzfuss, Dorit M. Hammerling
2025	J	`jnl`	Probabilistic Skip Connections for Deterministic Uncertainty Quantification in Deep Neural Networks. CoRR Felix Jimenez, Matthias Katzfuss
2025	J	`jnl`	Sparse Inverse Cholesky Factorization of Dense Kernel Matrices by Greedy Conditional Selection. SIAM/ASA J. Uncertain. Quantification Stephen Huan, Joseph Guinness, Matthias Katzfuss, Houman Owhadi, Florian Schäofer
2025	A	`conf`	Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks. AISTATS Felix Jimenez, Matthias Katzfuss
2023	J	`jnl`	Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference. Stat. Comput. Myeongjong Kang, Matthias Katzfuss
2023	A	`conf`	Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes. AISTATS Felix Jimenez, Matthias Katzfuss
2023	J	`jnl`	Sparse Cholesky factorization by greedy conditional selection. CoRR Stephen Huan, Joseph Guinness, Matthias Katzfuss, Houman Owhadi, Florian Schäfer
2023	A*	`conf`	Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization. ICML Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Tobias Schäfer, Matthias Katzfuss
2023	J	`jnl`	Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization. CoRR Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Schäfer, Matthias Katzfuss
2023	J	`jnl`	Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks. CoRR Felix Jimenez, Matthias Katzfuss
2022	J	`jnl`	Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering. Stat. Comput. Marcin Jurek, Matthias Katzfuss
2022	J	`jnl`	Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes. CoRR Felix Jimenez, Matthias Katzfuss
2022	J	`jnl`	Scalable Gaussian-process regression and variable selection using Vecchia approximations. J. Mach. Learn. Res. Jian Cao, Joseph Guinness, Marc G. Genton, Matthias Katzfuss
2022	J	`jnl`	Scaled Vecchia Approximation for Fast Computer-Model Emulation. SIAM/ASA J. Uncertain. Quantification Matthias Katzfuss, Joseph Guinness, Earl Lawrence
2022	J	`jnl`	Spatial Surface Reflectance Retrievals for Visible/Shortwave Infrared Remote Sensing via Gaussian Process Priors. Remote. Sens. Daniel Zilber, David R. Thompson, Matthias Katzfuss, Vijay Natraj, Jonathan Hobbs, Amy Braverman
2021	J	`jnl`	Multi-Resolution Filters for Massive Spatio-Temporal Data. J. Comput. Graph. Stat. Marcin Jurek, Matthias Katzfuss
2021	J	`jnl`	Sparse Cholesky Factorization by Kullback-Leibler Minimization. SIAM J. Sci. Comput. Florian Schäfer, Matthias Katzfuss, Houman Owhadi
2021	J	`jnl`	Spatial Retrievals of Atmospheric Carbon Dioxide from Satellite Observations. Remote. Sens. Jonathan Hobbs, Matthias Katzfuss, Daniel Zilber, Jenný Brynjarsdóttir, Anirban Mondal, Veronica J. Berrocal
2021	J	`jnl`	Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data. Comput. Stat. Data Anal. Daniel Zilber, Matthias Katzfuss
2020	J	`jnl`	Sparse Cholesky factorization by Kullback-Leibler minimization. CoRR Florian Schäfer, Matthias Katzfuss, Houman Owhadi
2017	J	`jnl`	Parallel inference for massive distributed spatial data using low-rank models. Stat. Comput. Matthias Katzfuss, Dorit Hammerling
2014	J	`jnl`	Spatio-Temporal Data Fusion for Very Large Remote Sensing Datasets. Technometrics Hai Nguyen, Matthias Katzfuss, Noel Cressie, Amy Braverman