deep-learning

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

Build, personalize and control your own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6

Repository for benchmarking graph neural networks (JMLR 2023)

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

FMA: A Dataset For Music Analysis

A toolkit to run Ray applications on Kubernetes

Image Deblurring using Generative Adversarial Networks

记录cv算法工程师的成长之路，分享计算机视觉和模型压缩部署技术栈笔记。https://harleyszhang.github.io/cv_note/

computer vision projects | 计算机视觉相关好玩的AI项目（Python、C++、embedded system）

Automatically remove the mosaics in images and videos, or add mosaics to them.

Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch

EdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCV 2019 https://arxiv.org/abs/1901.00212

🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.

Pytorch domain library for recommendation systems

**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring

A PyTorch Library for Multi-Task Learning

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking, Post Ranking, Relevance, LLM and RL. Please cite our paper "Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives" (TOIS 2026).

The PyTorch-based audio source separation toolkit for researchers

A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun