Pinned Repositories
AI-System
System for AI Education Resource.
awesome-chatgpt-prompts-zh
ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。
Awesome-DynamicGraphLearning
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs). 将深度学习技术(图神经网络等)应用在动态图、动态网络、动态知识图谱上的论文、工具等。
COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
craig
Data-efficient Training of Machine Learning Models
deep-active-learning
Deep Active Learning
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Orca
Code repository for the SIGMOD2023 paper "Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees".
Palette
Code repository for Palette, a multi-source model selection and ensemble framework.
Zebra
Code repository for the VLDB2023 paper "Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank".
LuckyLYM's Repositories
LuckyLYM/Zebra
Code repository for the VLDB2023 paper "Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank".
LuckyLYM/Orca
Code repository for the SIGMOD2023 paper "Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees".
LuckyLYM/Palette
Code repository for Palette, a multi-source model selection and ensemble framework.
LuckyLYM/AI-System
System for AI Education Resource.
LuckyLYM/awesome-chatgpt-prompts-zh
ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。
LuckyLYM/Awesome-DynamicGraphLearning
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs). 将深度学习技术(图神经网络等)应用在动态图、动态网络、动态知识图谱上的论文、工具等。
LuckyLYM/COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
LuckyLYM/craig
Data-efficient Training of Machine Learning Models
LuckyLYM/deep-active-learning
Deep Active Learning
LuckyLYM/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
LuckyLYM/EvolveGCN
Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
LuckyLYM/GNNPapers
Must-read papers on graph neural networks (GNN)
LuckyLYM/gpucb
Simple implementation of GP-UCB algorithm.
LuckyLYM/GraphSAINT
[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).
LuckyLYM/Incremental-Learning
LuckyLYM/Literatures-on-GNN-Acceleration
A reading list for deep graph learning acceleration.
LuckyLYM/luckylym.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
LuckyLYM/NAS
Works built upon DARTS
LuckyLYM/pytorch-sentiment-analysis
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
LuckyLYM/pytorch_geometric_temporal
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
LuckyLYM/Quantization
Data and model quantization
LuckyLYM/ray
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
LuckyLYM/reverb
Reverb is an efficient and easy-to-use data storage and transport system designed for machine learning research
LuckyLYM/seed_rl
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
LuckyLYM/TOC
Trie-based Matrix Compression