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Prune DNN using Alternating Direction Method of Multipliers (ADMM)
A defense algorithm which utilizes the combination of an auto- encoder and block-switching architecture. Auto-coder is intended to remove any perturbations found in input images whereas block switching method is used to make it more robust against White-box attack. Attack is planned using FGSM model, and the subsequent counter-attack by the proposed architecture will take place thereby demonstrating the feasibility and security delivered by the algorithm.
PyTorch implementation of adversarial attacks.
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Local Competition and Uncertainty for Adversarial Robustness
A PyTorch implementation of the method found in "Adversarially Robust Few-Shot Learning: A Meta-Learning Approach"
🧑🏫 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, ... 🧠
A review for latest few-shot learning works
😎 A curated list of awesome real-world adversarial examples resources
source code to ICLR'19, 'A Closer Look at Few-shot Classification'
Code release for ConvNeXt model
Official Implementation of Convolutional Normalization: Improving Robustness and Training for Deep Neural Networks
Copy-paste augmentation for segmentation and detection tasks
This is an official implementation for "Contextual Transformer Networks for Visual Recognition".
CVPR 2021 论文和开源项目合集
pytorch implementation of Parametric Noise Injection for adversarial defense
[CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long*, Luka Rimanic, Ce Zhang, Bo Li
deep learning for image processing including classification and object-detection etc.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
This repository contains implementations and illustrative code to accompany DeepMind publications
Developed with the UROP, Detecting Deep Learning Software Defects (Spring 2019), HKUST
A pytorch adversarial library for attack and defense methods on images and graphs
DeepXplore code release
代码 -《深度学习之PyTorch物体检测实战》
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.