xiangyu918's repositories
GraphMAE
GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
TinyWebServer
:fire: Linux下C++轻量级Web服务器学习
ParetoGNN
Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization
CSDI
Codes for "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation"
mtt-distillation
Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"
Source-Code-Notebook
关于一些经典论文源码的逐行中文笔记
pytorch-ts
PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend
AutoSSL
[ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"
embedx
embedx 是基于 c++ 开发的、完全自研的分布式 embedding 训练和推理框架。它目前支持 图模型、深度排序、召回模型和图与排序、图与召回的联合训练模型等
SAME
Code for the papers: "Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach", "A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings"
GraRep
A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).
OpenNE
An Open-Source Package for Network Embedding (NE)
TransGAN
[NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang
annotated_deep_learning_paper_implementations
🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
TransGAN-1
This is a re-implementation of TransGAN: Two Pure Transformers Can Make One Strong GAN (CVPR 2021) in PyTorch.
ImGAGN
Imbalanced Network Embedding vi aGenerative Adversarial Graph Networks
Lemane
Learning Based Proximity Matrix Factorization for Node Embedding
NRP-code
Code for Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank
transganformer
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
AROPE
This is the official implementation of "Arbitrary-Order Proximity Preserved Network Embedding"(KDD 2018).
HOPE
This is a sample implementation of "Asymmetric Transitivity Preserving Graph Embedding"(KDD 2016).