choprashweta / Adversarial-DebiasingLinks
Implementation of Adversarial Debiasing in PyTorch to address Gender Bias
☆31Updated 5 years ago
Alternatives and similar repositories for Adversarial-Debiasing
Users that are interested in Adversarial-Debiasing are comparing it to the libraries listed below
Sorting:
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆53Updated 3 years ago
- Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems☆74Updated 3 years ago
- ☆12Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 3 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.☆16Updated 5 years ago
- ☆89Updated 3 months ago
- ☆62Updated 4 years ago
- Influence Analysis and Estimation - Survey, Papers, and Taxonomy☆80Updated last year
- ⚖️ Code for the paper "Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning".☆11Updated 2 years ago
- ☆37Updated 2 years ago
- ☆38Updated 4 years ago
- This is a collection of papers and other resources related to fairness.☆95Updated 2 years ago
- ☆50Updated 2 years ago
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆29Updated 4 years ago
- ☆14Updated 5 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆50Updated 4 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- This repository holds code and other relevant files for the NeurIPS 2022 tutorial: Foundational Robustness of Foundation Models.☆71Updated 2 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆36Updated 3 years ago
- ☆95Updated 2 years ago
- https://arxiv.org/abs/2102.12594☆14Updated last year
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆83Updated 2 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 7 years ago
- ☆55Updated 4 years ago
- Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…☆25Updated 3 years ago
- ☆46Updated 2 years ago
- Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)☆13Updated 2 years ago
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆74Updated 2 years ago