Matthias Katzfuß

I am a Professor in the Department of Statistics at Texas A&M University.

I'm the recipient of an NSF Career Award, a Fulbright Scholarship, and an Early Investigator Award by the ASA Section on Statistics and the Environment.

Contact Information

Matthias Katzfuss

Department of Statistics

3143 TAMU

College Station, TX 77843

Email: katzfuss@gmail.com

Office: Blocker 467C

Recent group news:

  • 10/2022: Paul Wiemann is joining the group as a postdoc.

  • 9/2022: Paper on "Scalable Gaussian-process regression and variable selection using Vecchia approximations" accepted at Journal of Machine Learning Research. Preprint available on arXiv.

  • 9/2022: Paper on "High-dimensional nonlinear spatio-temporal filtering by compressing hierarchical sparse Cholesky factors" accepted at Journal of Data Science.

  • 9/2022: Paper on "Ordered conditional approximation of Potts models" accepted at Spatial Statistics.

  • 9/2022: Matthias has been promoted to (full) professor.

  • 8/2022: Paper on "Locally anisotropic covariance functions on the sphere" now on arXiv.

  • 7/2022: Paper on "Scalable spatio-temporal smoothing via hierarchical sparse Cholesky decomposition" accepted at Environmetrics.

  • 6/2022: Brian has completed his PhD. Congratulations!

  • 5/2022: We are looking for a postdoc to be funded by a newly awarded NASA grant. The position has been filled.

  • 3/2022: Paper on "Scalable Bayesian optimization using Vecchia approximations of Gaussian processes" now on arXiv.

  • 2/2022: Paper on "Scalable Gaussian-process regression and variable selection using Vecchia approximations" now on arXiv.

  • 1/2022: Matthias is chair of the ISBA Program Council for 2022.

  • 12/2021: Our paper on "Bayesian nonstationary and nonparametric covariance estimation for large spatial data" was selected as a discussion paper in Bayesian Analysis. Public contributions to the discussion can be made until Feb 9, 2022.

  • 12/2021: Paper on "Multi-scale Vecchia approximations of Gaussian processes" accepted at Journal of Agricultural, Biological, and Environmental Statistics.

  • 12/2021: Paper on "Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference" now on arXiv.

  • 12/2021: Paper on "Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering" accepted at Statistics and Computing.

  • 12/2021: Paper on "Scaled Vecchia approximation for fast computer-model emulation" accepted at SIAM/ASA Journal on Uncertainty Quantification.

  • 11/2021: Paper on "Nonstationary spatial modeling of massive global satellite data" now on arXiv.

  • 10/2021: Paper on "Ordered conditional approximation of Potts models" now on arXiv.

  • 8/2021: Paper on "Scalable Bayesian transport maps for high-dimensional non-Gaussian spatial fields" now on arXiv.

  • 6/2021: Daniel has completed his PhD and will work at NIH as a postdoc. Congratulations!

  • 5/2021: Paper on "Bayesian nonstationary and nonparametric covariance estimation for large spatial data" accepted at Bayesian Analysis.

  • 5/2021: Jian Cao has joined the group as a postdoc. Welcome!

  • 4/2021: Paper on "Ensemble Kalman filter updates based on regularized sparse inverse Cholesky factors" accepted at Monthly Weather Review.

  • 4/2021: Paper on "Interpretation of point forecasts with unknown directive" accepted at Journal of Applied Econometrics.

  • 2/2021: Paper on "Multi-resolution filters for massive spatio-temporal data" accepted at JCGS.

  • 2/2021: Paper on "Spatial retrievals of atmospheric carbon dioxide from satellite observations" accepted at Remote Sensing.

  • 1/2021: Matthias is now on the ISBA Program Council.

  • 1/2021: Paper on "Sparse Cholesky factorization by Kullback-Leibler minimization" accepted at SIAM Journal on Scientific Computing.

  • 1/2021: Jingjie's paper on "Multi-scale Vecchia approximations of Gaussian processes" was chosen as a top paper in the 2021 ENVR Student Paper Competition.

Older news items can be found here.