Alternatives and similar repositories for continuous-fairness

Users that are interested in continuous-fairness are comparing it to the libraries listed below

• charan223 / FairDeepLearning
  ☆37Updated 2 years ago
• lucweytingh / ARL-UvA
  A reproduced PyTorch implementation of the Adversarially Reweighted Learning (ARL) model, originally presented in "Fairness without Demog…
  ☆20Updated 4 years ago
• brandeis-machine-learning / awesome-ml-fairness
  Papers and online resources related to machine learning fairness
  ☆74Updated 2 years ago
• ahxt / fair_fairness_benchmark
  FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.
  ☆30Updated last year
• natalialmg / MMPF
  Implementation of Minimax Pareto Fairness framework
  ☆22Updated 5 years ago
• daviddao / awesome-data-valuation
  💱 A curated list of data valuation (DV) to design your next data marketplace
  ☆135Updated 9 months ago
• ryokamoi / pytorch_influence_functions
  This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…
  ☆17Updated 5 years ago
• steven7woo / fair_regression_reduction
  General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.
  ☆16Updated 5 years ago
• yuji-roh / fairbatch
  FairBatch: Batch Selection for Model Fairness (ICLR 2021)
  ☆20Updated 2 years ago
• opendataval / opendataval
  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
  ☆99Updated 10 months ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆51Updated 4 years ago
• yongkaiwu / FairAI
  This is a collection of papers and other resources related to fairness.
  ☆94Updated 3 weeks ago
• weitianxin / awesome-distribution-shift
  A curated list of papers and resources about the distribution shift in machine learning.
  ☆123Updated 2 years ago
• oscarkey / explanations-by-minimizing-uncertainty
  Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
  ☆19Updated 4 years ago
• alstonlo / torch-influence
  A simple PyTorch implementation of influence functions.
  ☆91Updated last year
• Viperccc / RDIA
  ☆18Updated 3 years ago
• nv-tlabs / DP-Sinkhorn_code
  ☆12Updated 3 years ago
• ZaydH / influence_analysis_papers
  Influence Analysis and Estimation - Survey, Papers, and Taxonomy
  ☆83Updated last year
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆72Updated last year
• baharanm / craig
  Data-efficient Training of Machine Learning Models
  ☆68Updated 4 years ago
• facebookresearch / certified-removal
  Certified Removal from Machine Learning Models
  ☆69Updated 4 years ago
• meghdadk / SCRUB
  ☆49Updated last year
• kaiwenzha / contrastive-poisoning
  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
  ☆32Updated 2 years ago
• nsfzyzz / boundary_thickness
  [NeurIPS 2020] code for "Boundary thickness and robustness in learning models"
  ☆20Updated 4 years ago
• jfc43 / informative-outlier-mining
  We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…
  ☆57Updated 3 years ago
• kohpangwei / group_DRO
  Distributionally robust neural networks for group shifts
  ☆286Updated 2 years ago
• acmi-lab / cmu-10732-robustness-adaptivity-shift
  Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments
  ☆77Updated 3 years ago
• OPTML-Group / Unlearn-WorstCase
  [ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, …
  ☆23Updated 6 months ago
• zdchu / CoNAL
  Code for AAAI 2021 long paper Learning from Crowds by Modeling Common Confusions.
  ☆11Updated 4 years ago
• zalanborsos / bilevel_coresets
  Coresets via Bilevel Optimization
  ☆68Updated 5 years ago