Convert ebooks to audiobooks with chapters and metadata using dynamic AI models and voice cloning. Supports 1,107+ languages!

PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译，支持 Google/DeepL/Ollama/OpenAI 等服务，提供 CLI/GUI/Docker

This is a repo with links to everything you'd ever want to learn about data engineering

CoTracker is a model for tracking any point (pixel) on a video.

MLコンペ用テンプレート

RAG that intelligently adapts to your use case, data, and queries

書籍『深層ニューラルネットワークの高速化』のサポートサイトです。

Pytorch implementation of various Knowledge Distillation (KD) methods.

⚡ Dynamically generated stats for your github readmes

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

💯 Curated coding interview preparation materials for busy software engineers

📚 List of awesome university courses for learning Computer Science!

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

Roadmap to becoming an Artificial Intelligence Expert in 2022

A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?

A list for GNNs and related works.

[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods

『推薦システム実践入門』のリポジトリ

「WandB で始める実験管理 - MLOps から LLMOps まで」に関する公開 Repository

All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.

Paper Lists for Graph Neural Networks

東京工業大学 traP Kaggle班「機械学習講習会」の資料

PyTorch Tutorial for Deep Learning Researchers

PyTorch公式チュートリアル（日本語翻訳版）の各ノートブックファイル（Google Colab用）です

A curated reading list of research in Mixture-of-Experts(MoE).

Gradient gating (ICLR 2023)

[NeurIPS'23] Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Rao Kompe…

How Powerful are Graph Neural Networks?

Implementation of Graph Convolutional Networks in TensorFlow