albermax / innvestigate
A toolbox to iNNvestigate neural networks' predictions!
☆1,286Updated last year
Alternatives and similar repositories for innvestigate:
Users that are interested in innvestigate are comparing it to the libraries listed below
- The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…☆332Updated 2 years ago
- A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…☆744Updated 4 years ago
- Interpretability Methods for tf.keras models with Tensorflow 2.x☆1,021Updated 8 months ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆584Updated last week
- Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).☆966Updated 11 months ago
- Public facing deeplift repo☆850Updated 2 years ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆209Updated 7 months ago
- Layer-wise Relevance Propagation (LRP) for LSTMs.☆222Updated 4 years ago
- Code for "High-Precision Model-Agnostic Explanations" paper☆798Updated 2 years ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆820Updated 2 years ago
- Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers☆97Updated 6 years ago
- Tensorflow tutorial for various Deep Neural Network visualization techniques☆348Updated 4 years ago
- ☆910Updated last year
- Attributing predictions made by the Inception network using the Integrated Gradients method☆611Updated 2 years ago
- Code for the TCAV ML interpretability project☆634Updated 6 months ago
- 👋 Xplique is a Neural Networks Explainability Toolbox☆664Updated 4 months ago
- Interpretability and explainability of data and machine learning models☆1,655Updated 7 months ago
- ☆572Updated last year
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,383Updated 2 months ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆133Updated 4 years ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization☆123Updated 8 months ago
- Visualization toolkit for neural networks in PyTorch! Demo -->☆738Updated last year
- Model interpretability and understanding for PyTorch☆5,080Updated this week
- The toolkit to explain Keras model predictions.☆15Updated 6 months ago
- Neural network visualization toolkit for tf.keras☆321Updated 10 months ago
- XAI - An eXplainability toolbox for machine learning☆1,153Updated 3 years ago
- Understanding Deep Networks via Extremal Perturbations and Smooth Masks☆345Updated 4 years ago
- Algorithms for explaining machine learning models☆2,447Updated 2 months ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆239Updated 6 months ago
- ☆264Updated 5 years ago