Alternatives and similar repositories for generative-attribution-methods

Users that are interested in generative-attribution-methods are comparing it to the libraries listed below

• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• ddkang / advex-uar
  Code for "Testing Robustness Against Unforeseen Adversaries"
  ☆80Updated last year
• 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 4 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…
  ☆128Updated 4 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆57Updated 5 years ago
• BeenKim / MMD-critic
  ☆135Updated 6 years ago
• Jianbo-Lab / L2X
  ☆125Updated 4 years ago
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆125Updated 4 years ago
• chihkuanyeh / Representer_Point_Selection
  code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018
  ☆67Updated 4 years ago
• dmadras / predict-responsibly
  ☆15Updated last year
• amiratag / InterpretationFragility
  Interpretation of Neural Network is Fragile
  ☆36Updated last year
• GDPlumb / MAPLE
  Supervised Local Modeling for Interpretability
  ☆29Updated 7 years ago
• ruthcfong / perturb_explanations
  Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"
  ☆32Updated 6 years ago
• aam-at / adversary_critic
  ☆13Updated 5 years ago
• zzzace2000 / FIDO-saliency
  Explaining Image Classifiers by Counterfactual Generation
  ☆28Updated 3 years ago
• gpleiss / equalized_odds_and_calibration
  Code and data for the experiments in "On Fairness and Calibration"
  ☆51Updated 3 years ago
• equialgo / fairness-in-ml
  This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
  ☆119Updated 4 years ago
• robust-ml / robust-ml.github.io
  A community-run reference for state-of-the-art adversarial example defenses.
  ☆51Updated last year
• peterbhase / InterpretableNLP-ACL2020
  Code for "Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?"
  ☆45Updated 2 years ago
• algofairness / fairness-comparison
  Comparing fairness-aware machine learning techniques.
  ☆161Updated 3 years ago
• google-research-datasets / bam
  ☆51Updated 5 years ago
• google / TrustScore
  To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…
  ☆178Updated 2 years ago
• evaluating-adversarial-robustness / adv-eval-paper
  LaTeX source for the paper "On Evaluating Adversarial Robustness"
  ☆259Updated 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…
  ☆77Updated 8 years ago
• chihkuanyeh / concept_exp
  code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"
  ☆54Updated 3 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago
• google-research / heldout-influence-estimation
  ☆62Updated 4 years ago
• max-andr / provably-robust-boosting
  Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]
  ☆50Updated 5 years ago
• grazianomita / machine_learning_interpretability_papers
  This is a public collection of papers related to machine learning model interpretability.
  ☆26Updated 4 years ago
• adebayoj / sanity_checks_saliency
  ☆113Updated 3 years ago