lapalap / B-LRP
B-LRP is the repository for the paper How Much Can I Trust You? — Quantifying Uncertainties in Explaining Neural Networks
☆18Updated 2 years ago
Alternatives and similar repositories for B-LRP:
Users that are interested in B-LRP are comparing it to the libraries listed below
- Self-Explaining Neural Networks☆42Updated 5 years ago
- ☆34Updated 4 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 4 years ago
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 4 years ago
- Combating hidden stratification with GEORGE☆63Updated 3 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆35Updated 2 years ago
- The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.☆40Updated 2 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆54Updated 2 years ago
- Repository for the paper "An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs"☆18Updated 5 years ago
- Fine-grained ImageNet annotations☆29Updated 4 years ago
- ☆17Updated 6 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 3 years ago
- Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters☆30Updated 4 years ago
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Updated 2 years ago
- 'Robust Semantic Interpretability: Revisiting Concept Activation Vectors' Official Implementation☆11Updated 4 years ago
- ☆45Updated 2 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- ☆35Updated last year
- Local explanations with uncertainty 💐!☆39Updated last year
- h-Shap provides an exact, fast, hierarchical implementation of Shapley coefficients for image explanations☆16Updated last year
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆31Updated 3 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
- ☆46Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆31Updated 3 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated 11 months ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆36Updated 4 years ago
- A TensorFlow implementation of the paper 'Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks'☆31Updated 11 months ago
- Label de-noising for deep learning☆58Updated 5 years ago