brandeis-machine-learning / awesome-ml-fairnessLinks
Papers and online resources related to machine learning fairness
☆75Updated 2 years ago
Alternatives and similar repositories for awesome-ml-fairness
Users that are interested in awesome-ml-fairness are comparing it to the libraries listed below
Sorting:
- This is a collection of papers and other resources related to fairness.☆95Updated 2 months ago
- ☆22Updated 6 years ago
- 💱 A curated list of data valuation (DV) to design your next data marketplace☆136Updated 11 months ago
- A reproduced PyTorch implementation of the Adversarially Reweighted Learning (ARL) model, originally presented in "Fairness without Demog…☆20Updated 4 years ago
- FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.☆31Updated last year
- ☆37Updated 2 years ago
- A curated list of trustworthy deep learning papers. Daily updating...☆381Updated last week
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 11 months ago
- A curated list of papers and resources about the distribution shift in machine learning.☆123Updated 2 years ago
- ☆33Updated 2 weeks ago
- ☆50Updated last year
- [ICML 2023] "On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation"☆23Updated 2 years ago
- Implementation of Minimax Pareto Fairness framework☆22Updated 5 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Updated 2 years ago
- ☆56Updated 3 years ago
- ☆27Updated 3 years ago
- [ICML 2023] "On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation"☆33Updated 2 years ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆69Updated 2 years ago
- [ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, …☆23Updated 7 months ago
- Paper List for Fair Graph Learning (FairGL).☆144Updated last year
- Data Optimization in Deep Learning: A Survey☆19Updated 2 years ago
- A curated collection of adversarial attack and defense on recommender systems.☆136Updated 3 years ago
- Methods for removing learned data from neural nets and evaluation of those methods☆38Updated 5 years ago
- Certified Removal from Machine Learning Models☆69Updated 4 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆31Updated 2 years ago
- translation of VHL repo in paddle☆25Updated 2 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Updated 4 years ago
- Code repository for the paper "Invariant and Transportable Representations for Anti-Causal Domain Shifts"☆16Updated 3 years ago
- Code for 'CausalAdv: Adversarial Robustness Through the Lens of Causality'☆43Updated 2 years ago
- [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…☆80Updated last year