Alternatives and similar repositories for predict-responsibly

Users that are interested in predict-responsibly are comparing it to the libraries listed below

• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• steven7woo / fair_regression_reduction
  General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.
  ☆16Updated 4 years ago
• clinicalml / learn-to-defer
  Code for "Consistent Estimators for Learning to Defer to an Expert" (ICML 2020)
  ☆13Updated 2 years ago
• js-d / sim_metric
  ☆35Updated last year
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆40Updated last year
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆52Updated last year
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• google-research / heldout-influence-estimation
  ☆62Updated 3 years ago
• izmailovpavel / spurious_feature_learning
  ☆45Updated 2 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆55Updated 4 years ago
• geifmany / uncertainty_ICLR
  Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019
  ☆13Updated 6 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆34Updated 3 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago
• Angie-Liu / labelshift
  Regularized Learning under label shifts
  ☆18Updated 6 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 4 years ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 3 years ago
• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• dmelis / SENN
  Self-Explaining Neural Networks
  ☆13Updated last year
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆36Updated 2 years ago
• zzzace2000 / FIDO-saliency
  Explaining Image Classifiers by Counterfactual Generation
  ☆28Updated 3 years ago
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆31Updated 4 years ago
• chihkuanyeh / concept_exp
  code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"
  ☆53Updated 3 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆49Updated 3 years ago
• yixinwang / representation-causal-public
  ☆44Updated 3 years ago