ahxt / fair_fairness_benchmarkLinks
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.
β30Updated last year
Alternatives and similar repositories for fair_fairness_benchmark
Users that are interested in fair_fairness_benchmark are comparing it to the libraries listed below
Sorting:
- β22Updated 6 years ago
- π± A curated list of data valuation (DV) to design your next data marketplaceβ127Updated 7 months ago
- Papers and online resources related to machine learning fairnessβ73Updated 2 years ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)β99Updated 7 months ago
- Implementation of Minimax Pareto Fairness frameworkβ21Updated 5 years ago
- A curated list of papers and resources about the distribution shift in machine learning.β123Updated 2 years ago
- General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.β16Updated 5 years ago
- This is a collection of papers and other resources related to fairness.β95Updated 2 years ago
- A reproduced PyTorch implementation of the Adversarially Reweighted Learning (ARL) model, originally presented in "Fairness without Demogβ¦β20Updated 4 years ago
- β29Updated last week
- [ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, β¦β22Updated 4 months ago
- A simple PyTorch implementation of influence functions.β91Updated last year
- Code for paper: Are Large Language Models Post Hoc Explainers?β33Updated last year
- This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influenceβ¦β17Updated 5 years ago
- Influence Analysis and Estimation - Survey, Papers, and Taxonomyβ82Updated last year
- Data-efficient Training of Machine Learning Modelsβ66Updated 4 years ago
- β26Updated 2 years ago
- β13Updated 2 years ago
- β37Updated 2 years ago
- [ICML 2021] "A Unified Lottery Tickets Hypothesis for Graph Neural Networks", Tianlong Chen*, Yongduo Sui*, Xuxi Chen, Aston Zhang, Zhangβ¦β67Updated last year
- Official implementation of GOAT model (ICML2023)β38Updated 2 years ago
- β47Updated last year
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".β28Updated 3 years ago
- Training-free data valuation on deep neural network applications. (ICML-2022)β26Updated 3 years ago
- [NeurIPS 2021] code for "Taxonomizing local versus global structure in neural network loss landscapes" https://arxiv.org/abs/2107.11228β19Updated 3 years ago
- Certified Removal from Machine Learning Modelsβ69Updated 4 years ago
- Towards Efficient Shapley Value Estimation via Cross-contribution Maximizationβ14Updated 3 years ago
- Paper List for Fair Graph Learning (FairGL).β141Updated last year
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)β49Updated 2 years ago
- Official Code Repository for the paper - Personalized Subgraph Federated Learning (ICML 2023)β49Updated 2 years ago