Horseshoe regression model fitted in PyMC.

The Method of Entropic Regression, sparse system identification method based on causality inference of complex networks.

A Python Package for a Sparse Additive Boosting Regressor

Self-concordant Smoothing for Large-Scale Convex Composite Optimization

Factored QTL analysis applied to GTEx and GWAS of 114 complex traits

Implemented and Compared Algorithms Solving Sparse Penalized Regression

Physically-informed model discovery of systems with nonlinear, rational terms using the SINDy-PI method. Contains functionality for spectral filtering/differentiation.

Generalized Orthogonal Least-Squares in CUDA

Выпускная квалификационная работа бакалавра

This work presents the application of machine learning models in order to obtain a sparse governing equation of complex fluid dynamics problems.

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."

code for performing Bayesian ARD regression, where covariates have groups

Assignment: Linear and Sparse Regression Consider the attached dataset about advertising and sales. The attributes denote the investments on advertising in TV, radio etc and the target variable is the total sales. The aim is to predict the sales from the investments on advertising. 1) Randomly divide the dataset into training (75%) and testing (…

Physics-informed refinement learning for equation discovery

Automatic hyperparameter selection for Lasso-like models solving the M/EEG source localization problem

Simple implementation of (Takada & Fujisawa, 2020, NeurIPS) and (Takada & Fujisawa, 2023, arXiv)

(now superseded by MLJLinearModels)

Nonconvex Exterior Point Operator Splitting

Robust regression algorithm that can be used for explaining black box models (R implementation)