Algorithms for outlier, adversarial and drift detection
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Updated
Aug 5, 2024 - Python
Algorithms for outlier, adversarial and drift detection
《深度学习与计算机视觉》配套代码
An information security preparedness tool to do adversarial simulation.
Sentiment Analysis, Text Classification, Text Augmentation, Text Adversarial defense, etc.;
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation
Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
Stochastic Adversarial Video Prediction
💡 Adversarial attacks on explanations and how to defend them
Adversarial Training for Natural Language Understanding
Crafting adversarial images
Adversarial Texture Optimization from RGB-D Scans (CVPR 2020).
Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.
Code and pretrained models for paper: Data-Free Adversarial Distillation
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification. https://aclanthology.org/2021.acl-long.381/
A PyTorch implementation of adversarial pose estimation for multi-person
[Nature Machine Intelligence Journal] Official pytorch implementation for Uncertainty-Guided Dual-Views for Semi-Supervised Volumetric Medical Image Segmentation
Torch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)
A checkers reinforcement learning AI, and all the tools needed to train it.
RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
Implementation of adversarial training under fast-gradient sign method (FGSM), projected gradient descent (PGD) and CW using Wide-ResNet-28-10 on cifar-10. Sample code is re-usable despite changing the model or dataset.
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