52 Open source projects that are alternatives of or similar to adversarial-vision-challenge

A Closer Look at Accuracy vs. Robustness

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

Adversarial Distributional Training (NeurIPS 2020)

Source code and dataset for the CCKS201 paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"

Robust error-handling for Kotlin and Android

Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation （ICCV2021）

RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)

A curated list of awesome resources regarding machine learning reliability.

Scaleable input gradient regularization

Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".

[ICML 2021] A fast algorithm for fitting robust decision trees. http://proceedings.mlr.press/v139/vos21a.html

[CVPR 2022] S-attack library. Official implementation of two papers "Vehicle trajectory prediction works, but not everywhere" and "Are socially-aware trajectory prediction models really socially-aware?".

Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)

Contains code for the paper "Vision Transformers are Robust Learners" (AAAI 2022).

Code and models for ICCV2021 paper "Robust Object Detection via Instance-Level Temporal Cycle Confusion".

Adversarial Attacks on Deep Neural Networks for Time Series Classification

Code for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"

Code to reproduce the attacks and defenses for the entries "JeromeR" in the NIPS 2018 Adversarial Vision Challenge

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

Code used during my Chaos Engineering and Resiliency Patterns talk.

Code for NeurIPS 2019 Paper

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

[NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: A Unified Optimization Framework”

adversarial examples, adversarial malware examples, adversarial malware detection, adversarial deep ensemble, Android malware variants

Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Reachability analysis for closed-loop control systems

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

Benchmarks for Corruption Invariant Person Re-identification. [NeurIPS 2021 Track on Datasets and Benchmarks]

Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs

Randomized Smoothing of All Shapes and Sizes (ICML 2020).

Sensor data aggregation tool for any numerical sensor data. Robust and privacy-friendly.

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"

阿里云MNS

An Algorithm to Quantify Robustness of Recurrent Neural Networks

Code for the unrestricted adversarial examples paper (NeurIPS 2018)

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Minimal implementation of Denoised Smoothing (https://arxiv.org/abs/2003.01908) in TensorFlow.

A curated (most recent) list of resources for Learning with Noisy Labels

[NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

Implemention of Fast Gradient Sign Method for generating adversarial examples in Keras

Recentrifuge: robust comparative analysis and contamination removal for metagenomics

PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Generative Forests in Python

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

Paper list of Adversarial Examples

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).