mndu / guided-feature-inversion
PyTorch code for KDD 18 paper: Towards Explanation of DNN-based Prediction with Guided Feature Inversion
☆21Updated 6 years ago
Alternatives and similar repositories for guided-feature-inversion:
Users that are interested in guided-feature-inversion are comparing it to the libraries listed below
- Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing the…☆55Updated 2 years ago
- Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network☆62Updated 5 years ago
- A general method for training cost-sensitive robust classifier☆22Updated 5 years ago
- Interpretation of Neural Network is Fragile☆36Updated 10 months ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆44Updated 5 years ago
- An (imperfect) implementation of wide resnets and Parseval regularization☆9Updated 4 years ago
- Implementation of our NeurIPS 2018 paper: Deep Defense: Training DNNs with Improved Adversarial Robustness☆39Updated 6 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- Reverse Cross Entropy for Adversarial Detection (NeurIPS 2018)☆45Updated 3 years ago
- Adversarial learning by utilizing model interpretation☆10Updated 6 years ago
- Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)☆16Updated 2 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- ☆25Updated 5 years ago
- This repository is for NeurIPS 2018 spotlight paper "Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples."☆31Updated 2 years ago
- Interval attacks (adversarial ML)☆21Updated 5 years ago
- An Algorithm to Quantify Robustness of Recurrent Neural Networks☆47Updated 4 years ago
- Adversarial Defense for Ensemble Models (ICML 2019)☆61Updated 4 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 4 years ago
- ☆19Updated 3 years ago
- Detect adversarial images from intermediate features in distance space☆12Updated 6 years ago
- Code for Stability Training with Noise (STN)☆21Updated 4 years ago
- code we used in Decision Boundary Analysis of Adversarial Examples https://openreview.net/forum?id=BkpiPMbA-☆27Updated 6 years ago
- ☆18Updated 5 years ago
- Research prototype of deletion efficient k-means algorithms☆23Updated 5 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆15Updated 4 years ago
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]☆18Updated 6 years ago
- ☆26Updated 2 years ago
- Code for paper "Dimensionality-Driven Learning with Noisy Labels" - ICML 2018☆58Updated 9 months ago
- Tensorflow code for "Hierarchical Decompositional Mixtures of Variational Autoencoders" (ICML'19)☆12Updated 4 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago