| Multi-resolution filters for massive spatio-temporal data M Jurek, M Katzfuss Journal of Computational and Graphical Statistics 30 (4), 1095-1110, 2021 | 28 | 2021 |
| Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering M Jurek, M Katzfuss Statistics and Computing 32 (1), 15, 2022 | 18 | 2022 |
| GPvecchia: Fast Gaussian-process inference using Vecchia approximations M Katzfuss, M Jurek, D Zilber, W Gong, J Guinness, J Zhang, F Schäfer R package version 0.1 3, 2020 | 14 | 2020 |
| GPvecchia: Scalable gaussian-process approximations M Katzfuss, M Jurek, D Zilber, W Gong R package version 0.1 3, 2020 | 9 | 2020 |
| Scalable spatio‐temporal smoothing via hierarchical sparse Cholesky decomposition M Jurek, M Katzfuss Environmetrics 34 (1), e2757, 2023 | 6 | 2023 |
| Parallel Implementation of the Multi-resolution Approximation for Large-scale Spatial Gaussian Models in Python M Jurek, DM Hammerling http://dx.doi.org/10.26024/c04h-fd33, 2018 | 2 | 2018 |
| Statistical inference for complete and incomplete mobility trajectories under the flight-pause model M Jurek, CA Calder, C Zigler Journal of the Royal Statistical Society Series C: Applied Statistics 73 (1 …, 2024 | 1 | 2024 |
| Improving Selection Accuracy of Maize (Zea mays L.)Â Grain Yield Utilizing Unmanned Aerial Systems and Structure from Motion Height Estimates in the Central … S Anderson, L Malambo, A Chang, M Jurek, S Popescu, J Jung, D Cope, ... Plant and Animal Genome XXVII Conference (January 12-16, 2019), 2019 | | 2019 |
| Implementation of Unmanned Aerial Systems as a Tool in the Texas Maize (Zea mays L.) Breeding Program S Anderson, L Malambo, A Chang, M Jurek, S Popescu, J Jung, D Cope, ... Plant and Animal Genome XXVII Conference (January 12-16, 2019), 2019 | | 2019 |
Matthias KatzfussProfessor of Statistics, University of Wisconsin–Madison在 wisc.edu 的电子邮件经过验证
