pankessel / adv_explanation_refLinks
reference implementation for "explanations can be manipulated and geometry is to blame"
☆37Updated 3 years ago
Alternatives and similar repositories for adv_explanation_ref
Users that are interested in adv_explanation_ref are comparing it to the libraries listed below
Sorting:
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆54Updated 3 years ago
- Original dataset release for CIFAR-10H☆82Updated 5 years ago
- ☆72Updated 5 years ago
- ☆37Updated 2 years ago
- ☆51Updated 5 years ago
- ☆112Updated 3 years ago
- This repository provides a PyTorch implementation of "Fooling Neural Network Interpretations via Adversarial Model Manipulation". Our pap…☆23Updated 4 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆42Updated last year
- Adversarially Robust Neural Network on MNIST.☆63Updated 3 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…☆25Updated 3 years ago
- Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".☆56Updated 3 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆141Updated 5 years ago
- Explaining Image Classifiers by Counterfactual Generation☆28Updated 3 years ago
- ☆43Updated last year
- Concept Bottleneck Models, ICML 2020☆233Updated 2 years ago
- Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?☆40Updated 3 years ago
- Implemented CURE algorithm from robustness via curvature regularization and vice versa☆32Updated 3 years ago
- Towards Automatic Concept-based Explanations☆161Updated last year
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- ☆142Updated 5 years ago
- ☆160Updated 4 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆80Updated last year
- Detect model's attention☆169Updated 5 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated 2 years ago
- Crowdsourcing metrics and test datasets beyond ImageNet (ICML 2022 workshop)☆38Updated last year
- [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data☆112Updated 5 years ago
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆25Updated last year
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆96Updated 4 years ago
- ☆55Updated 5 years ago