sparse-modeling

Replication code and hash-traced artifacts for sparse pair and triple interaction support selection.

Sparse modeling tool for analytical continuation of imaginary-time Green's function

PyTorch implementation of sparse Bayesian factor analysis: closed-form mean-field variational objective, ARD factor selection, graph-Laplacian priors for spatial smoothness, and identifiability-aware evaluation with calibration diagnostics (CRPS, PIT). Synthetic benchmarks.

A header-only C++ library for solving Sparse Principal Component Analysis Problems & a standalone Application Software named Sparsely.

A header-only C++ library for solving Sparse Modeling Problems via Biconjugate Convex Relaxation Techniques.

Interactive Python implementation of https://arxiv.org/pdf/2001.08496

A machine learning algorithm to create risk score models for risk prediction

Efficient Algorithms for L0 Regularized Learning

Python implementation of the sparse clustering methods

Python 3 environment for benchmarking PRIISM

Python 3 environment for tnakazato/priism (on ADC/MDAS)

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

Sparse modeling and Compressive sensing in Python

A Python library for sGMRFmix model for anomaly detection in time series

Sparse Gaussian graphical models with Sorted L-One Penalized Estimation

Library for faster pinned CPU <-> GPU transfer in Pytorch

STELA algorithm for sparsity regularized linear regression (LASSO)

Code for the paper "Learning sparse transformations through backpropagation"

Implementing machine learning models from scratch for Sentiment Analysis on movie reviews