Alternatives and similar repositories for lime-experiments:

Users that are interested in lime-experiments are comparing it to the libraries listed below

• marcotcr / anchor
  Code for "High-Precision Model-Agnostic Explanations" paper
  ☆802Updated 2 years ago
• BeenKim / MMD-critic
  ☆134Updated 5 years ago
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆82Updated 2 years ago
• Jianbo-Lab / L2X
  ☆125Updated 3 years ago
• marcoancona / DeepExplain
  A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…
  ☆750Updated 4 years ago
• ankurtaly / Integrated-Gradients
  Attributing predictions made by the Inception network using the Integrated Gradients method
  ☆624Updated 3 years ago
• mbilalzafar / fair-classification
  Python code for training fair logistic regression classifiers.
  ☆189Updated 3 years ago
• sebastian-lapuschkin / lrp_toolbox
  The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…
  ☆332Updated 2 years ago
• kundajelab / deeplift
  Public facing deeplift repo
  ☆853Updated 3 years ago
• lopusz / awesome-interpretable-machine-learning
  ☆916Updated 2 years ago
• algofairness / fairness-comparison
  Comparing fairness-aware machine learning techniques.
  ☆159Updated 2 years ago
• ArrasL / LRP_for_LSTM
  Layer-wise Relevance Propagation (LRP) for LSTMs.
  ☆224Updated 5 years ago
• VigneshSrinivasan10 / interprettensor
  ☆100Updated 7 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 4 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆128Updated 3 years ago
• mkusner / counterfactual-fairness
  Code for "Counterfactual Fairness" (NIPS2017)
  ☆53Updated 6 years ago
• suinleelab / treeexplainer-study
  Code and documentation for experiments in the TreeExplainer paper
  ☆185Updated 5 years ago
• riccotti / LORE
  LOcal Rule-based Exlanations
  ☆53Updated last year
• equialgo / fairness-in-ml
  This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
  ☆117Updated 4 years ago
• ustunb / actionable-recourse
  python tools to check recourse in linear classification
  ☆76Updated 4 years ago
• algofairness / BlackBoxAuditing
  Research code for auditing and exploring black box machine-learning models.
  ☆132Updated last year
• amarasovic / interpretability-literature
  ☆264Updated 5 years ago
• marcotcr / anchor-experiments
  Experiments for AAAI anchor paper
  ☆63Updated 7 years ago
• laura-rieger / deep-explanation-penalization
  Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…
  ☆127Updated 4 years ago
• kohpangwei / influence-release
  ☆791Updated 4 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆55Updated 4 years ago
• h2oai / mli-resources
  H2O.ai Machine Learning Interpretability Resources
  ☆488Updated 4 years ago
• marcoancona / DASP
  Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)
  ☆61Updated 5 years ago
• cosmicBboy / themis-ml
  A library that implements fairness-aware machine learning algorithms
  ☆124Updated 4 years ago
• dtak / tree-regularization-public
  Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"
  ☆78Updated 7 years ago