understandable-machine-intelligence-lab / QuantusLinks
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
☆624Updated 2 months ago
Alternatives and similar repositories for Quantus
Users that are interested in Quantus are comparing it to the libraries listed below
Sorting:
- 👋 Xplique is a Neural Networks Explainability Toolbox☆702Updated 11 months ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆233Updated 2 months ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆247Updated last year
- OmniXAI: A Library for eXplainable AI☆952Updated last year
- MetaQuantus is an XAI performance tool to identify reliable evaluation metrics☆39Updated last year
- A Library for Uncertainty Quantification.☆920Updated 5 months ago
- A toolbox to iNNvestigate neural networks' predictions!☆1,303Updated 5 months ago
- ☆488Updated last year
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆295Updated 2 years ago
- For calculating global feature importance using Shapley values.☆276Updated this week
- Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty i…☆266Updated 2 weeks ago
- Reliability diagrams visualize whether a classifier model needs calibration☆158Updated 3 years ago
- A collection of research materials on explainable AI/ML☆1,560Updated this week
- 👋 Influenciae is a Tensorflow Toolbox for Influence Functions☆64Updated last year
- Experiments on Tabular Data Models☆279Updated 2 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆432Updated last week
- Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layers☆100Updated 6 months ago
- 💡 Adversarial attacks on explanations and how to defend them☆328Updated 10 months ago
- ☆122Updated 3 years ago
- A toolkit for quantitative evaluation of data attribution methods.☆53Updated 2 months ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆366Updated last year
- The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive …☆451Updated 3 years ago
- A framework for prototyping and benchmarking imputation methods☆196Updated 2 years ago
- ☆207Updated 4 years ago
- Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human…☆74Updated 3 years ago
- scikit-activeml: A Comprehensive and User-friendly Active Learning Library☆173Updated 2 weeks ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,446Updated 2 months ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆138Updated 4 years ago
- A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…☆755Updated 5 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆248Updated 2 years ago