Muhammad Muaz's Projects
30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace.
Repository for storing codebase of course project of '3D Humans'
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
My Implementation of Adversarial Diffusion Distillation https://arxiv.org/pdf/2311.17042.pdf
A beautiful, simple, clean, and responsive Jekyll theme for academics
Algorithm Design (Kleinberg Tardos 2005) - Solutions
Popular algorithms explained in simple language with examples and links to their implementation in various programming languages and other required resources.
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
Personal Website (using Quarto)
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
Repository for Meta Chameleon, a mixed-modal early-fusion foundation model from FAIR.
Clone of COGMEN Repository for Speech, Language Technologies course
A comprehensive catalog of modern and classic books on C++ programming language
Forked repository of Spring 2019 CS-388G Algorithms course
Computer Organization and Architecture
š¤ Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
my dotfiles based on catppuccin theme
Fine tune stable video diffusion.
Generative Models by Stability AI
Neovim motions on speed!
Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference
All 180 problem solutions
A mirror for all the links I post on my personal discord server
[NeurIPS'23 Oral] Visual Instruction Tuning: LLaVA (Large Language-and-Vision Assistant) built towards GPT-4V level capabilities.
A collection of infrastructure and tools for research in neural network interpretability.
My Personal Special Repository
This repository contains algorithms written in MATLAB/Octave. Developing algorithms in the MATLAB environment empowers you to explore and refine ideas, and enables you test and verify your algorithm.