fastFMM - Fast Functional Mixed Models using Fast Univariate Inference
Implementation of the fast univariate inference approach (Cui et al. (2022) <doi:10.1080/10618600.2021.1950006>, Loewinger et al. (2024) <doi:10.7554/eLife.95802.2>) for fitting functional mixed models. User guides and Python package information can be found at <https://github.com/gloewing/photometry_FLMM>.
Last updated 7 days ago
6.51 score 9 stars 22 scripts 398 downloadssMTL - Sparse Multi-Task Learning
Implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) <arXiv:2212.08697>.
Last updated 2 years ago
1.00 score 8 scripts 155 downloads