Popular GitHub Repositories for Growing

AingDesk是一款简单好用的AI助手，支持知识库、模型API、分享、联网搜索、智能体，它还在飞快成长中。 AingDesk is a simple and easy-to-use AI assistant that supports knowledge bases, model APIs, sharing, internet search, and intelligent agents. It is still growing rapidly.

:fire::fire: PyTorch implementation of "Progressive growing of GANs (PGGAN)" :fire::fire:

PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.

A growing curation of Text-to-3D, Diffusion-to-3D works.

T2F: text to face generation using Deep Learning

Unofficial PyTorch implementation of the paper titled "Progressive growing of GANs for improved Quality, Stability, and Variation"

Image segmentation - general superpixel segmentation & center detection & region growing

A reproduction of growing neural cellular automata using PyTorch.

Metorial MCP Index - An ever growing list of open source MCP servers ? ?

MSG-GAN: Multi-Scale Gradients GAN (Architecture inspired from ProGAN but doesn't use layer-wise growing)

Tensorflow implementation of PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION

Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen, "Compacting, Picking and Growing for Unforgetting Continual Learning," Thirty-third Conference on Neural Information Processing Systems, NeurIPS 2019

A PyTorch 0.4 implementation of Progressive Growing of GANs for Improved Quality, Stability and Variability (https://arxiv.org/abs/1710.10196)

We're excited to be your gateway into machine learning. ML is a rapidly growing field that's buzzing with opportunity.

Welcome! ? This is the working draft of the Aalto Dictionary of Machine Learning (ADictML) — a growing collection of short, clear definitions for key terms in machine learning.

Examples trained using the python pytorch package pro-gan-pth

Torch implementation of "PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION"

Pure tensorflow implementation of progressive growing of GANs

PyTorch implementation of A Style-Based Generator Architecture for Generative Adversarial Network

A carefully curated collection of high-quality libraries, projects, tutorials, research papers, and other essential resources focused on Mechanistic Interpretability, a growing subfield in machine learning interpretability research that aims to reverse-engineer neural networks into understandable computational components.