leader120's repositories
AIJack
Security and Privacy Risk Simulator for Machine Learning
Awesome-Domain-LLM
收集和梳理垂直领域的开源模型、数据集及评测基准。
Awesome-Federated-Learning-on-Graph-and-GNN-papers
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.
awesome-imbalanced-learning-on-graphs
A repository contains a collection of resources and papers on Imbalance Learning On Graphs
Differential-Privacy-Based-Federated-Learning
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )
DynamicPFL
nips23-Dynamic Personalized Federated Learning with Adaptive Differential Privacy
erase
[Arxiv-2023] Official code for work "ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance"
Fed-NCL
Federated Noisy Client Learning
FedCorr
CVPR 2022: FedCorr: Multi-Stage Federated Learning for Label Noise Correction
FPL_MS
a MindSpore implementation of Federated Prototype Learning
GNN-VPA
A Variance-Preserving Aggregation Strategy for Graph Neural Networks
Graph-Neural-Networks-With-Heterophily
This repository contains the resources on graph neural network (GNN) considering heterophily.
graph-papers
Graph Neural Network, Self-Supervised Learning, Contrastive Learning, RecSys, Transformer Papers Reading Notes.
GSLB
A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)
HtFL
You only need to configure one file to support model heterogeneity scenarios.
MarsFL
Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark
NoisyGL
A Comprehensive Benchmark for Graph Neural Networks under Label Noise
PFLlib
Personalized federated learning simulation platform with non-IID and unbalanced dataset
POT-GCL
Source code of NeurIPS 2023 "Provable Training for Graph Contrastive Learning"
ProG
All in One: Multi-task Prompting for Graph Neural Networks, KDD 2023.
pytorch_geometric
Graph Neural Network Library for PyTorch
RGIB
[NeurIPS 2023] "Combating Bilateral Edge Noise for Robust Link Prediction"
RNCGLN
This is the implement of RNCGLN which paper is submitted to AAAI24
SFA
The official implementation for paper: Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels
SupContrast
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
TAM
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification