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addressing-class-imbalance-fl

This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

advances-in-label-noise-learning

A curated (most recent) list of resources for Learning with Noisy Labels

advbox

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

adversarial-attacks-pytorch

PyTorch implementation of adversarial attacks.

adversarial-example-attack-and-defense

This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.

adversarial-model-inversion

Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)

age

aijack

Security and Privacy Risk Simulator for Machine Learning

am-gcn

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks

autogcl

AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)

awesome-cv-writing

该仓库包含了计算机视觉论文中写作常用的句式、短语、缩写等。

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-gnn-research

My future research

awesome-imbalanced-learning-on-graphs

A repository contains a collection of resources and papers on Imbalance Learning On Graphs

bkd_fedgnn

Implementation of paper "More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks"

brgcl-code

cagcn

This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".

capsnet-tensorflow

A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules

casitlab

读研不迷茫。。。。

cdr

ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels

channelwise-saab-transform

Feature extraction (Module 1) for PixelHop/PixelHop++

channelwise-saab-transform-1

Copy from USC-MCL EE569

clga

Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22

co-learning-learning-from-noisy-labels-with-self-supervision

The official implementation of the ACM MM'2021 paper Co-learning: Learning from noisy labels with self-supervision.

contrastiveleaks

creff-fl

cs-gnn

Measuring and Improving the Use of Graph Information in Graph Neural Networks

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

dca-nips2017

Differentially private learning on distributed data (NIPS 2017)