amparore / leafLinks
A Python framework for the quantitative evaluation of eXplainable AI methods
☆17Updated 2 years ago
Alternatives and similar repositories for leaf
Users that are interested in leaf are comparing it to the libraries listed below
Sorting:
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆139Updated 4 years ago
- Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems☆75Updated 3 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆85Updated 3 years ago
- Papers and code of Explainable AI esp. w.r.t. Image classificiation☆225Updated 3 years ago
- ☆122Updated 3 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆252Updated last year
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- ☆12Updated 2 years ago
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆25Updated last year
- 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 package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpreta…☆380Updated 3 years ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆238Updated 4 months ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆634Updated 4 months ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆70Updated 2 years ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization☆139Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆162Updated 3 years ago
- A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.☆100Updated 3 years ago
- Detect model's attention☆169Updated 5 years ago
- An amortized approach for calculating local Shapley value explanations☆104Updated 2 years ago
- Dataset and code for the CLEVR-XAI dataset.☆33Updated 2 years ago
- TensorFlow 2 implementation of the paper Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution …☆45Updated 4 years ago
- ☆18Updated 2 years ago
- Pytorch implementation of various neural network interpretability methods☆119Updated 3 years ago
- ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021☆106Updated 3 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆255Updated 2 years ago
- Meaningful Local Explanation for Machine Learning Models☆42Updated 2 years ago
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Updated 3 years ago
- Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human…☆74Updated 3 years ago
- 💡 Adversarial attacks on explanations and how to defend them☆330Updated last year
- Explaining Anomalies Detected by Autoencoders Using SHAP☆44Updated 4 years ago