Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"
☆187Sep 17, 2020Updated 5 years ago
Alternatives and similar repositories for constructed-datasets
Users that are interested in constructed-datasets are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code for "Robustness May Be at Odds with Accuracy"☆90Mar 24, 2023Updated 3 years ago
- Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"☆163Mar 19, 2020Updated 6 years ago
- A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.☆942Jan 11, 2024Updated 2 years ago
- TRADES (TRadeoff-inspired Adversarial DEfense via Surrogate-loss minimization)☆552Mar 30, 2023Updated 3 years ago
- A challenge to explore adversarial robustness of neural networks on CIFAR10.☆510Aug 30, 2021Updated 4 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Analysis of Adversarial Logit Pairing☆60Aug 13, 2018Updated 7 years ago
- ImageNet classifier with state-of-the-art adversarial robustness☆683Dec 31, 2019Updated 6 years ago
- LaTeX source for the paper "On Evaluating Adversarial Robustness"☆260Apr 16, 2021Updated 5 years ago
- A Toolbox for Adversarial Robustness Research☆1,368Sep 14, 2023Updated 2 years ago
- Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"☆129Oct 24, 2019Updated 6 years ago
- This repository provides simple PyTorch implementations for adversarial training methods on CIFAR-10.☆173Feb 17, 2021Updated 5 years ago
- Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".☆13Sep 11, 2020Updated 5 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Dec 8, 2022Updated 3 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆140Mar 30, 2020Updated 6 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Official code for FAccT'21 paper "Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning" https://arxiv.org/abs…☆13Mar 9, 2021Updated 5 years ago
- PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.☆254Aug 26, 2020Updated 5 years ago
- A challenge to explore adversarial robustness of neural networks on MNIST.☆764May 3, 2022Updated 4 years ago
- Visualization of Adversarial Examples☆34Oct 14, 2018Updated 7 years ago
- Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples☆907Jun 10, 2023Updated 2 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆73Jun 1, 2024Updated last year
- Contest Proposal and infrastructure for the Unrestricted Adversarial Examples Challenge☆334Sep 17, 2020Updated 5 years ago
- A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX☆2,958Dec 3, 2025Updated 5 months ago
- Empirical tricks for training robust models (ICLR 2021)☆258May 25, 2023Updated 2 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is a robustness metric for deep neural networks☆63Aug 3, 2021Updated 4 years ago
- Related papers for robust machine learning☆562May 25, 2023Updated 2 years ago
- A community-run reference for state-of-the-art adversarial example defenses.☆52Oct 13, 2024Updated last year
- Implementation of AlphaZero in PyTorch.☆10Apr 19, 2019Updated 7 years ago
- For Competition on Adversarial Attacks and Defenses 2018☆39Jan 4, 2019Updated 7 years ago
- Adversarially Robust Transfer Learning with LWF loss applied to the deep feature representation (penultimate) layer☆19Feb 9, 2020Updated 6 years ago
- This is the reading list mainly on adversarial examples (attacks, defenses, etc.) I try to keep and update regularly.☆227Oct 7, 2019Updated 6 years ago
- Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"☆744May 16, 2024Updated 2 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆31Jul 15, 2020Updated 5 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- ☆22Oct 5, 2023Updated 2 years ago
- First-Order Adversarial Vulnerability of Neural Networks and Input Dimension☆15Sep 4, 2019Updated 6 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30May 16, 2022Updated 4 years ago
- Robust evasion attacks against neural network to find adversarial examples☆863Jun 1, 2021Updated 4 years ago
- [ICLR 2020] A repository for extremely fast adversarial training using FGSM☆446Jul 25, 2024Updated last year
- A method for training neural networks that are provably robust to adversarial attacks.☆392Feb 16, 2022Updated 4 years ago
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆24May 10, 2019Updated 7 years ago