Alternatives and similar repositories for rrr

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

• BeenKim / MMD-critic
  ☆134Updated 6 years ago
• gpleiss / equalized_odds_and_calibration
  Code and data for the experiments in "On Fairness and Calibration"
  ☆51Updated 3 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 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
• Jianbo-Lab / L2X
  ☆124Updated 4 years ago
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆124Updated 4 years ago
• IBM / Contrastive-Explanation-Method
  Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…
  ☆54Updated 7 years ago
• GDPlumb / MAPLE
  Supervised Local Modeling for Interpretability
  ☆29Updated 6 years ago
• google-research / heldout-influence-estimation
  ☆62Updated 4 years ago
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆58Updated 4 years ago
• HazyResearch / hidden-stratification
  Combating hidden stratification with GEORGE
  ☆64Updated 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…
  ☆76Updated 7 years ago
• algofairness / fairness-comparison
  Comparing fairness-aware machine learning techniques.
  ☆159Updated 2 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 5 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 3 years ago
• kundajelab / abstention
  Algorithms for abstention, calibration and domain adaptation to label shift.
  ☆37Updated 4 years ago
• equialgo / fairness-in-ml
  This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
  ☆118Updated 4 years ago
• dmadras / predict-responsibly
  ☆14Updated last year
• ServiceNow / synbols
  The Synbols dataset generator is a ServiceNow Research project that was started at Element AI.
  ☆45Updated 2 years ago
• SeojinBang / VIBI
  Explaining a black-box using Deep Variational Information Bottleneck Approach
  ☆46Updated 2 years ago
• adebayoj / sanity_checks_saliency
  ☆111Updated 2 years ago
• IBM / SIC
  Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019
  ☆14Updated 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
  ☆29Updated 4 years ago
• zzzace2000 / FIDO-saliency
  Explaining Image Classifiers by Counterfactual Generation
  ☆28Updated 3 years ago
• ustunb / actionable-recourse
  python tools to check recourse in linear classification
  ☆78Updated 4 years ago
• lsgos / uncertainty-adversarial-paper
  Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
  ☆61Updated 7 years ago
• google-research-datasets / bam
  ☆51Updated 5 years ago
• tonyduan / rs4a
  Randomized Smoothing of All Shapes and Sizes (ICML 2020).
  ☆51Updated 5 years ago
• marcotcr / anchor-experiments
  Experiments for AAAI anchor paper
  ☆63Updated 7 years ago