Matthias Katzfuß
I am a Professor in the Department of Statistics at University of Wisconsin–Madison.
I'm a Fellow of the American Statistical Association, and 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
University of Wisconsin–Madison
Email: katzfuss@gmail.com
Office: 1171 Medical Sciences Center
Recent group news:
9/2024: Paper on "Learning non-Gaussian spatial distributions via Bayesian transport maps with parametric shrinkage" now on arXiv.
8/2024: Anirban has completed his PhD. Congratulations!
8/2024: Matthias was named Fellow of the American Statistical Association.
7/2024: Matthias has joined the Board of Directors of the ASA Wisconsin Chapter.
6/2024: Paper on "Scalable sampling of truncated multivariate normals using sequential nearest-neighbor approximation" now on arXiv.
1/2024: Paper on "Asymptotic properties of Vecchia approximation for Gaussian processes" now on arXiv.
11/2023: Paper on "Linear-cost Vecchia approximation of multivariate normal probabilities" now on arXiv.
10/2023: Paper on "Bayesian nonparametric generative modeling of large multivariate non-Gaussian spatial fields" accepted at JABES.
9/2023: Paper on "Locally anisotropic nonstationary covariance functions on the sphere" accepted at JABES.
8/2023: Matthias has joined the Department of Statistics at UW–Madison.
7/2023: MJ has completed his PhD. Congratulations!
5/2023: Paper on "Vecchia Gaussian process ensembles on internal representations of deep neural networks" now on arXiv.
4/2023: Paper on "Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization" accepted at ICML.
3/2023: Paper on "Scalable Bayesian transport maps for high-dimensional non-Gaussian spatial fields" accepted at JASA T&M.
3/2023: Paper on "Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference" accepted at Statistics and Computing.
1/2023: Paper on "Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization" now on arXiv.
1/2023: Paper on "Scalable Bayesian optimization using Vecchia approximations of Gaussian processes" accepted at AISTATS.
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.
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.