lapalap / B-LRPLinks
B-LRP is the repository for the paper How Much Can I Trust You? — Quantifying Uncertainties in Explaining Neural Networks
☆18Updated 3 years ago
Alternatives and similar repositories for B-LRP
Users that are interested in B-LRP are comparing it to the libraries listed below
Sorting:
- Combating hidden stratification with GEORGE☆64Updated 4 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
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 5 years ago
- ☆38Updated 5 years ago
- Active and Sample-Efficient Model Evaluation☆26Updated 6 months ago
- Tools for training explainable models using attribution priors.☆124Updated 4 years ago
- ☆17Updated 6 years ago
- Self-Explaining Neural Networks☆43Updated 5 years ago
- The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.☆40Updated 3 years ago
- Fine-grained ImageNet annotations☆30Updated 5 years ago
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆101Updated 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
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆36Updated 3 years ago
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Updated 3 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆37Updated 5 years ago
- Visual Explanation using Uncertainty based Class Activation Maps☆23Updated 5 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- Reusable BatchBALD implementation☆79Updated last year
- Quantile risk minimization☆24Updated last year
- Gradient Starvation: A Learning Proclivity in Neural Networks☆60Updated 4 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆55Updated 3 years ago
- Code to study the generalisability of benchmark models on non-stationary EHRs.☆14Updated 6 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆42Updated 3 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 4 years ago
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆30Updated 4 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- Multislice PHATE for tensor embeddings☆61Updated 4 years ago