junhua's Stars
dair-ai/Prompt-Engineering-Guide
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
mli/paper-reading
深度学习经典、新论文逐段精读
pyg-team/pytorch_geometric
Graph Neural Network Library for PyTorch
thunlp/GNNPapers
Must-read papers on graph neural networks (GNN)
eugeneyan/open-llms
📋 A list of open LLMs available for commercial use.
TypeCellOS/BlockNote
A React Rich Text Editor that's block-based (Notion style) and extensible. Built on top of Prosemirror and Tiptap.
microsoft/promptbase
All things prompt engineering
naganandy/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
andrewyng/translation-agent
pinecone-io/examples
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
vintasoftware/django-react-boilerplate
Django 5, React, Bootstrap 5 with Python 3 and Webpack project boilerplate
openai/openai-assistants-quickstart
OpenAI Assistants API quickstart with Next.js.
jwwthu/GNN4Traffic
This is the repository for the collection of Graph Neural Network for Traffic Forecasting.
tum-pbs/pbdl-book
Welcome to the Physics-based Deep Learning Book (v0.2)
seongjunyun/Graph_Transformer_Networks
Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
Lionelsy/Conference-Accepted-Paper-List
Some Conferences' accepted paper lists (including AI, ML, Robotic)
Spijkervet/SimCLR
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.
lucidrains/iTransformer
Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group
jwwthu/GNN-Communication-Networks
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
CroitoruAlin/Diffusion-Models-in-Vision-A-Survey
This repository categorizes the papers about diffusion models applied in computer vision according to their target task. The classifcation is based on our survey: https://arxiv.org/abs/2209.04747v1
THUDM/GCC
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
hantsy/angular-spring-reactive-sample
RESTful API demos with Spring 6 WebFlux, Spring Boot 3, Spring Data Mongo, Spring Security, Spring Session and Angular (upgraded to v16)
junhua/UOL-OOP-CM2005
xiezhq-hermann/graphiler
Graphiler is a compiler stack built on top of DGL and TorchScript which compiles GNNs defined using user-defined functions (UDFs) into efficient execution plans.
WangXuhongCN/APAN
HKUDS/AutoST
[WWW'2023] "AutoST: Automated Spatio-Temporal Graph Contrastive Learning"
Graph-Machine-Learning-Group/sgp
Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)
Graph-Machine-Learning-Group/spin
Official repository for the paper "Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations" (NeurIPS 2022)
RManLuo/GSNOP
Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
lfunderburk/automate-tech-post
LLM application: fine tuned model to generate social media posts from technical blogposts. I used the documentation in https://numpy.org/numpy-tutorials/index.html to build a synthetic dataset and used that dataset to fine-tune an open source model.