DJjjjhao / MarginGANLinks
This repository is the replication package of the NeurIPS19 paper "MarginGAN: Adversarial Training in Semi-Supervised Learning"
☆12Updated 6 years ago
Alternatives and similar repositories for MarginGAN
Users that are interested in MarginGAN are comparing it to the libraries listed below
Sorting:
- Reverse Cross Entropy for Adversarial Detection (NeurIPS 2018)☆47Updated 4 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks☆66Updated 6 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- ☆108Updated 3 years ago
- [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning☆85Updated 3 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 5 years ago
- Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)☆125Updated 2 years ago
- Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)☆71Updated 6 years ago
- [CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks☆124Updated 5 years ago
- Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"☆143Updated 5 years ago
- Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks☆242Updated 4 years ago
- PyTorch library for adversarial attack and training☆145Updated 6 years ago
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Updated 3 years ago
- [CVPR 2020] Code for paper "AdversarialNAS: Adversarial Neural Architecture Search for GANs".☆72Updated 2 years ago
- 🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.☆105Updated 6 years ago
- PyTorch implementation of Weighted Batch-Normalization layers☆37Updated 5 years ago
- PyTorch implementation of "Feature Denoising for Improving Adversarial Robustness" on CIFAR10.☆35Updated 5 years ago
- Meta-Learning based Noise-Tolerant Training☆123Updated 5 years ago
- ☆26Updated 6 years ago
- Implementation "Adapting Auxiliary Losses Using Gradient Similarity" article☆32Updated 6 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago
- Code for the paper "Training CNNs with Selective Allocation of Channels" (ICML 2019)☆25Updated 6 years ago
- [ECCV 2018] Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study☆39Updated 3 years ago
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆81Updated 6 years ago
- This is the code of CVPR'20 paper "Distilling Cross-Task Knowledge via Relationship Matching".☆49Updated 4 years ago
- An unofficial implementation of 《Deep Mutual Learning》 by Pytorch to do classification on cifar100.☆168Updated 5 years ago
- Code for NeurIPS 2019 Paper☆48Updated 5 years ago
- Source Code for ICML 2019 Paper "Shallow-Deep Networks: Understanding and Mitigating Network Overthinking"☆37Updated last year
- Adversarial Defense for Ensemble Models (ICML 2019)☆61Updated 4 years ago