[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
☆125Dec 29, 2021Updated 4 years ago
Alternatives and similar repositories for AugMax
Users that are interested in AugMax are comparing it to the libraries listed below
Sorting:
- This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".☆46Nov 6, 2022Updated 3 years ago
- [NeurIPS 2022] "Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets" by Ruisi Cai*, Zhenyu Zh…☆21Oct 1, 2022Updated 3 years ago
- ☆21Nov 19, 2021Updated 4 years ago
- Official implementation of "Removing Batch Normalization Boosts Adversarial Training" (ICML'22)☆19Jul 20, 2022Updated 3 years ago
- Code for the paper "SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness" (NeurIPS 2021)☆21Sep 27, 2022Updated 3 years ago
- Code and models for the paper Shape-Texture Debiased Neural Network Training (ICLR 2021)☆111Aug 4, 2023Updated 2 years ago
- [NeurIPS'22] Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. Haotao Wang, Junyuan Hong,…☆15Nov 27, 2023Updated 2 years ago
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆17Mar 29, 2023Updated 2 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty☆988Mar 12, 2026Updated last week
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30May 16, 2022Updated 3 years ago
- Adversarial Distributional Training (NeurIPS 2020)☆63Mar 17, 2021Updated 5 years ago
- Adversarially Robust Transfer Learning with LWF loss applied to the deep feature representation (penultimate) layer☆19Feb 9, 2020Updated 6 years ago
- [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers☆22Feb 20, 2022Updated 4 years ago
- Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)☆40Dec 6, 2021Updated 4 years ago
- A Self-Consistent Robust Error (ICML 2022)☆69Jun 25, 2023Updated 2 years ago
- Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image cor…☆62May 24, 2023Updated 2 years ago
- [ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain☆80Sep 15, 2022Updated 3 years ago
- [NeurIPS 2020] code for "Boundary thickness and robustness in learning models"☆20Dec 11, 2020Updated 5 years ago
- This is the code for semi-supervised robust training (SRT).☆18Mar 24, 2023Updated 2 years ago
- [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang☆116Dec 30, 2021Updated 4 years ago
- [NeurIPS 2024] Efficiency for Free: Ideal Data Are Transportable Representations☆19Jan 19, 2025Updated last year
- ☆12May 6, 2022Updated 3 years ago
- ICLR 2023 paper "Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness" by Yuancheng Xu, Yanchao Sun, Micah Gold…☆25May 2, 2023Updated 2 years ago
- ImageNet-R(endition) and DeepAugment (ICCV 2021)☆280Jul 23, 2021Updated 4 years ago
- LISA for ICML 2022☆52Apr 12, 2023Updated 2 years ago
- Code for the ICCV 2023 paper "Benchmarking Low-Shot Robustness to Natural Distribution Shifts"☆11Jan 21, 2024Updated 2 years ago
- Codes for ICCV 2021 paper "AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Met…☆12Mar 3, 2022Updated 4 years ago
- ☆23Jun 15, 2022Updated 3 years ago
- [CVPR 2022] This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.☆157Dec 6, 2022Updated 3 years ago
- [Preprint] "In Defense of the Triplet Loss Again: Learning Robust Person Re-Identification with Fast Approximated Triplet Loss and Label …☆44Dec 31, 2021Updated 4 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59May 24, 2019Updated 6 years ago
- Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"☆741May 16, 2024Updated last year
- source code for paper "Accelerate Learning of Deep Hashing With Gradient Attention" (ICCV 2019)☆11Jan 14, 2020Updated 6 years ago
- Code for the paper Adversarial Robustness via Adversarial Label-Smoothing☆11Feb 5, 2020Updated 6 years ago
- Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"☆189Feb 18, 2021Updated 5 years ago
- Dataset accompanying the paper "Adaptive Methods for Real-World Domain Generalization"☆16Aug 17, 2023Updated 2 years ago
- Official PyTorch implementation of "Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup" (ICML'20)☆155Nov 25, 2021Updated 4 years ago
- A PyTorch implementation of "Meta-Amortized Variational Inference and Learning" (https://arxiv.org/abs/1902.01950)☆14Mar 31, 2020Updated 5 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆139Mar 30, 2020Updated 5 years ago