guxizhi

guxizhi's Stars

• guxizhi/SpanGNN

  SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training

  Language:Python3

• shaoyx/UniNet

  Language:C++311

• zhao-tong/GAug

  AAAI'21: Data Augmentation for Graph Neural Networks

  Language:Python18634

• Oldpan/Pytorch-Memory-Utils

  pytorch memory track code

  Language:Python1k155

• flyingdoog/PGExplainer

  Parameterized Explainer for Graph Neural Network

  Language:Jupyter Notebook12515

• GraphSAINT/GraphSAINT

  [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

  Language:Python47187

• GATECH-EIC/BNS-GCN

  [MLSys 2022] "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling" by Cheng Wan, Youjie Li, Ang Li, Nam Sung Kim, Yingyan Lin

  Language:Python5110

• staoxiao/LibVQ

  Language:Python701

• EnyanDai/RSGNN

  An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))

  Language:Python325

• DuoLife-QNL/GraSorw

  An I/O-Efficient Disk-based Graph System for Scalable Second-Order RandomWalk of Large Graphs

  Language:C++253

• HenryChang213/dgNN

  Language:Python1

• chwan1016/awesome-gnn-systems

  A list of awesome GNN systems.

  Language:Python28325

• dmlc/dgl

  Python package built to ease deep learning on graph, on top of existing DL frameworks.

  Language:Python13.5k3k

• IntelLabs/SAR

  Language:Python349

• GATECH-EIC/PipeGCN

  [ICLR 2022] "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication" by Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

  Language:Python307

• jiazhihao/HAG

  Language:TeX1

• pyg-team/pytorch_geometric

  Graph Neural Network Library for PyTorch

  Language:Python21.3k3.6k

• eastmountyxz/Knowledge-Graph-Movie

  本资源为作者知识图谱实战博客对应资源，采用HTML+D3+JSON搭建电影数据库。该资源也是网易云张老师的学习总结，希望对您有所帮助。文章博客为：https://blog.csdn.net/Eastmount/article/details/87371200

  Language:HTML6628

• acbull/LADIES

  Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"

  Language:Python7619

• GraphSAINT/GraphACT

  [FPGA 2020] Open sourced implementation for the ACM/SIGDA FPGA '20 paper titled "GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms"

  Language:Python174

• VictorYXL/MyOS

  Language:C29766