mar

PyGrinder: a Python toolkit for grinding data beans into the incomplete for real-world data simulation by introducing missing values with different missingness patterns, including MCAR (complete at random), MAR (at random), MNAR (not at random), sub sequence missing, and block missing

[ICCV2025]LazyMAR: Accelerating Masked Autoregressive Models via Feature Caching

A Noesis plugin to load textured models and animations from the master collection versions of MGS2 and MGS3

A One stop solution of Solutions for Ds and Algo and DSML for #scalerDSMLmar2022 batch students.

My personal simpler alternative to mdbook

This program is used to decompress and compress MAR archives used in Fossil Fighters game.

A library for synthetic missing data generation.

Welcome to visit my profile! ❤️❤️❤️❤️

How Different Types of Missingness affect a complete Dataset

Simple uncompressed random access archive format

Repositorio con enunciados, casos de prueba y soluciones de problemas de MAR2.

Healthcare missing-data analysis comparing complete-case, KNN, Bayesian iterative, and multiple imputation under MCAR, MAR, and MNAR.

Implementation of IEC 60601-2-44 Ed.4 Annex GG for objective evaluation of CT Metal Artifact Reduction (MAR) using DDOG CHO and AUC analysis.

1603:16:504 🇲🇦

Documents of the project

FAI (Feature-Wise Adaptive Imputation) is a machine learning framework that automatically selects the best imputation method per feature based on statistical properties — optimizing for downstream predictive performance, not just imputation error.

Bootcamp learning python on the zero-to-mastery platform

A comparative study of missing data imputation methods across MCAR, MAR, and MNAR mechanisms using classical, probabilistic, and deep learning approaches.

Pronóstico del Tiempo personalizado en Torre del Mar

This is my website using GitHub Pages and markdown.