A package for the sparse identification of nonlinear dynamical systems from data
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Updated
Nov 7, 2024 - Python
A package for the sparse identification of nonlinear dynamical systems from data
Efficient Algorithms for L0 Regularized Learning
Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)
a collection of modern sparse (regularized) linear regression algorithms.
MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3
Statistical Models with Regularization in Pure Julia
Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian learning, and basis pursuit.
Matlab toolbox for sparse regression
Sorted L1 Penalized Estimation
Sequential adaptive elastic net (SAEN) approach, complex-valued LARS solver for weighted Lasso/elastic-net problems, and sparsity (or model) order detection with an application to single-snapshot source localization.
Nonconvex Exterior Point Operator Splitting
Variable Selection and Task Grouping for Multi-Task Learning (VSTG-MTL)
Black-box spike and slab variational inference, example with linear models
Actually Sparse Variational Gaussian Processes implemented in GPlow
locus R package - Large-scale variational inference for variable selection in sparse multiple-response regression
Sparse Identification of Truncation Errors (SITE) for Data-Driven Discovery of Modified Differential Equations
Knowledge elicitation when the user can give feedback to different features of the model with the goal to improve the prediction on the test data in a "smal n, large p" setting.
Physically-informed model discovery of systems with nonlinear, rational terms using the SINDy-PI method. Contains functionality for spectral filtering/differentiation.
MGLM Toolbox for Matlab
Sparse Bayesian ARX models with flexible noise distributions
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