yunyuntsai / Black-box-Adversarial-ReprogrammingLinks
Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (ICML 2020)
☆38Updated 4 years ago
Alternatives and similar repositories for Black-box-Adversarial-Reprogramming
Users that are interested in Black-box-Adversarial-Reprogramming are comparing it to the libraries listed below
Sorting:
- [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…☆82Updated 3 years ago
- Smooth Adversarial Training☆68Updated 4 years ago
- [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…☆125Updated 3 years ago
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆21Updated 3 years ago
- Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”☆42Updated 4 years ago
- Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"☆142Updated 5 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Code for Active Mixup in 2020 CVPR☆23Updated 3 years ago
- "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).☆51Updated 4 years ago
- Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, N…☆75Updated last year
- [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…☆68Updated 2 years ago
- [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning☆85Updated 3 years ago
- Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image cor…☆61Updated 2 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
- Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)☆39Updated 3 years ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆56Updated 3 years ago
- Evaluating AlexNet features at various depths☆40Updated 4 years ago
- Zero-Shot Knowledge Distillation in Deep Networks☆67Updated 3 years ago
- ☆35Updated 4 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 4 years ago
- [TPAMI 2019] The implementation for "Direction Concentration Learning: Enhancing Congruency in Machine Learning"☆23Updated 5 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆105Updated 4 years ago
- ☆19Updated 4 years ago
- Compressing Representations for Self-Supervised Learning☆78Updated 4 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆45Updated 5 years ago
- Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes☆23Updated 5 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- PyTorch Implementation of CVPR'19 (oral) - Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach☆28Updated 5 years ago
- ☆108Updated 3 years ago