A package for the sparse identification of nonlinear dynamical systems from data
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Updated
May 8, 2024 - Python
A package for the sparse identification of nonlinear dynamical systems from data
Nonconvex Exterior Point Operator Splitting
Self-concordant Smoothing for Large-Scale Convex Composite Optimization
Simple implementation of (Takada & Fujisawa, 2020, NeurIPS) and (Takada & Fujisawa, 2023, arXiv)
code for performing Bayesian ARD regression, where covariates have groups
Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. To appear in the Proceedings of the Royal Society A.
Horseshoe regression model fitted in PyMC.
Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)
Methods for data segmentation under a sparse regression model
Efficient Algorithms for L0 Regularized Learning
locus R package - Large-scale variational inference for variable selection in sparse multiple-response regression
A Python Package for a Sparse Additive Boosting Regressor
Robust regression algorithm that can be used for explaining black box models (Python implementation)
Sorted L1 Penalized Estimation
Robust regression algorithm that can be used for explaining black box models (R implementation)
Actually Sparse Variational Gaussian Processes implemented in GPlow
Выпускная квалификационная работа бакалавра
The official respository for noise-aware physics-informed machine learning (nPIML)
This repository is the official implementation of "A Comparative Study on Machine Learning Algorithms for Knowledge Discovery."
The Python Implementation of Sparse Regression.
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