JADEXIN's starred repositories
GraphSAINT
[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).
Awesome-GNN-Research
My future research
graphsage-simple
Simple reference implementation of GraphSAGE.
large-scale-GNN
这项目主要收集大规模GNN(图神经网络)的相关研究
ClusterGCN
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
google-research
Google Research
entity-matchers
Source code for "A Critical Re-evaluation of Neural Methods for Entity Alignment"
PromptPapers
Must-read papers on prompt-based tuning for pre-trained language models.
OpenEA-TF2
Migrated OpenEA on TFv2.4.1
NLP_ability
总结梳理自然语言处理工程师(NLP)需要积累的各方面知识,包括面试题,各种基础知识,工程能力等等,提升核心竞争力
attacking_federate_learning
基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型