rtflynn / Cifar-Autoencoder
A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.
☆64Updated 6 years ago
Alternatives and similar repositories for Cifar-Autoencoder:
Users that are interested in Cifar-Autoencoder are comparing it to the libraries listed below
- This is a reimplementation of the blog post "Building Autoencoders in Keras". Instead of using MNIST, this project uses CIFAR10.☆72Updated 6 years ago
- This is an implementation of the VAE (Variational Autoencoder) for Cifar10☆72Updated 3 years ago
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆96Updated 3 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆141Updated 5 years ago
- Code for the unrestricted adversarial examples paper (NeurIPS 2018)☆64Updated 5 years ago
- Code for the paper "Understanding Generalization through Visualizations"☆60Updated 4 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"☆147Updated 4 years ago
- Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".☆55Updated 3 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 3 years ago
- PyTorch implementations of Adversarial defenses and utils.☆34Updated last year
- Robust Out-of-distribution Detection in Neural Networks☆72Updated 3 years ago
- A Self-Consistent Robust Error (ICML 2022)☆67Updated last year
- RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)☆56Updated 4 years ago
- ☆140Updated 4 years ago
- Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…☆96Updated 3 years ago
- Code for the paper "Consistency Regularization for Certified Robustness of Smoothed Classifiers" (NeurIPS 2020)☆34Updated 4 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆46Updated 3 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆59Updated 5 years ago
- Code for the paper "Adversarial Self-supervised Contrastive Learning" (NeurIPS 2020)☆171Updated 2 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"☆160Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆73Updated 10 months ago
- A pytorch re-implementation for paper "Towards Deep Learning Models Resistant to Adversarial Attacks"☆19Updated 5 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 5 years ago
- Source Code for ICRL 2018 Paper: PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples☆25Updated 5 years ago
- Code for the paper "On the Adversarial Robustness of Visual Transformers"☆56Updated 3 years ago