猫不理狗子's Projects
AISystem 主要是指AI系统,包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
A collection of AWESOME things about Graph-Related LLMs.
A curated list of papers and resources based on "Large Language Models on Graphs: A Comprehensive Survey".
🔥🔥🔥Latest Papers, Codes and Datasets on Vid-LLMs.
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
A professionally curated list of awesome resources (paper, code, data, etc.) on Self-Supervised Learning for Time Series (SSL4TS).
list of papers, code, and other resources
A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.
LibCity: An Open Library for Urban Spatial-temporal Data Mining
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Python package built to ease deep learning on graph, on top of existing DL frameworks.
DSPy: The framework for programming—not prompting—foundation models
[SIGIR 2024] This is the official PyTorch implementation for the paper: "EulerFormer: Sequential User Behavior Modeling with Complex Vector Attention".
Repository for G-Retriever
Implementation of Graph Convolutional Networks in TensorFlow
Software in C and data files for the popular GloVe model for distributed word representations, a.k.a. word vectors or embeddings
[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 Kompella, Zhangyang Wang
Graph based retrieval + GenAI = Better RAG in production
GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
A modular graph-based Retrieval-Augmented Generation (RAG) system
One-click deploy of a Knowledge Graph powered RAG (GraphRAG) in Azure
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.
Unify Efficient Fine-Tuning of 100+ LLMs