chihkuanyeh / saliency_evaluationLinks
Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for evaluating any saliency explanations.
☆25Updated 3 years ago
Alternatives and similar repositories for saliency_evaluation
Users that are interested in saliency_evaluation 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
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆71Updated 4 years ago
- ☆46Updated 4 years ago
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- ☆51Updated 5 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 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
- ☆38Updated 4 years ago
- ☆21Updated 2 years ago
- Interpretation of Neural Network is Fragile☆36Updated last year
- Explaining Image Classifiers by Counterfactual Generation☆28Updated 3 years ago
- ☆112Updated 2 years ago
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks☆231Updated 6 years ago
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆101Updated 3 years ago
- Original dataset release for CIFAR-10H☆82Updated 5 years ago
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 7 years ago
- This repository provides a PyTorch implementation of "Fooling Neural Network Interpretations via Adversarial Model Manipulation". Our pap…☆23Updated 4 years ago
- ☆72Updated 5 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".☆348Updated 6 years ago
- Self-Supervised Learning for OOD Detection (NeurIPS 2019)☆267Updated 4 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆92Updated 5 years ago
- Code for the Paper 'On the Connection Between Adversarial Robustness and Saliency Map Interpretability' by C. Etmann, S. Lunz, P. Maass, …☆16Updated 6 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 4 years ago
- Quantitative Testing with Concept Activation Vectors in PyTorch☆43Updated 6 years ago
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago