Alternatives and similar repositories for machine_learning_interpretability_papers:

Users that are interested in machine_learning_interpretability_papers are comparing it to the libraries listed below

• GDPlumb / MAPLE
  Supervised Local Modeling for Interpretability
  ☆28Updated 6 years ago
• Jianbo-Lab / L2X
  ☆125Updated 3 years ago
• SinaMohseni / ML-Interpretability-Evaluation-Benchmark
  This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data
  ☆30Updated 3 years ago
• MarcelRobeer / ContrastiveExplanation
  Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University
  ☆45Updated 2 years ago
• lydiatliu / delayedimpact
  Code for reproducing results in Delayed Impact of Fair Machine Learning (Liu et al 2018)
  ☆14Updated 2 years ago
• hrayrhar / T-CorEx
  Implementation of linear CorEx and temporal CorEx.
  ☆37Updated 3 years ago
• csinva / disentangled-attribution-curves
  Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
  ☆27Updated 4 years ago
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆59Updated 3 years ago
• gpleiss / equalized_odds_and_calibration
  Code and data for the experiments in "On Fairness and Calibration"
  ☆51Updated 2 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆55Updated 4 years ago
• wangtongada / BOA
  Bayesian or-of-and
  ☆34Updated 3 years ago
• yaringal / acquisition_example
  Train a simple convnet on the MNIST dataset and evaluate the BALD acquisition function
  ☆16Updated 7 years ago
• jphall663 / xai_misconceptions
  Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!
  ☆28Updated 5 years ago
• eelenberg / streak
  Interpreting neural networks via the STREAK algorithm (streaming weak submodular maximization)
  ☆23Updated 7 years ago
• andrewk1 / pytorch-deep-bayesian-bandits
  PyTorch port and extension of the Deep Bayesian Bandits Library
  ☆42Updated 5 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆99Updated 4 years ago
• OscarcarLi / PrototypeDL
  Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…
  ☆74Updated 7 years ago
• RobRomijnders / bandit
  Implementation of Counterfactual risk minimization
  ☆26Updated 7 years ago
• kundajelab / abstention
  Algorithms for abstention, calibration and domain adaptation to label shift.
  ☆36Updated 4 years ago
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆30Updated 4 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• peterbhase / InterpretableNLP-ACL2020
  Code for "Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?"
  ☆46Updated last year
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆123Updated 4 years ago
• hamaadshah / gan_tensorflow
  Automatic feature engineering using Generative Adversarial Networks using TensorFlow.
  ☆51Updated 2 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• ermongroup / BiasAndGeneralization
  ☆26Updated 5 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆128Updated 3 years ago
• blei-lab / context-selection-embedding
  Context Selection for Embedding Models
  ☆27Updated 7 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 3 years ago
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆29Updated 6 years ago