A collection of used public baseline & dataset links in my past research.
- MEDFAIR: MEDFAIR: Benchmarking Fairness for Medical Imaging. ICLR 2023 Spotlight.
- CXR-Fairness: A fairness benchmark on Chest X-rays classification with multiple baselines methods, including ERM, Balanced ERM, Adversarial, MMDMatch, MeanMatch, FairALM, GroupDRO, ARL, JTT.
- PARADE: Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in DML. ICLR 2022. [Code on OpenReview]
- BR-Net: Representation Learning with Statistical Independence to Mitigate Bias. WACV 2021.
- Orth: Fairness by Learning Orthogonal Disentangled Representations. ECCV 2020.
- FFVAE: Flexibly Fair Representation Learning by Disentanglement. ICML 2019. [A easy-to-use third-party implementation recommended by the author]
- SSPL: Partial Label Learning with Unlabeled Data. IJCAI 2019. [An offcial implementation using Matlab from LAMDA group]
- PARM: Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization. NeurIPS 2020.
- Prostate: A non-iid FL dataset for MRI prostate segmentation including 6 institutions
- FeTS 2022 Challenge: A non-iid FL dataset for MRI brain tumor segmentation from RSNA-ASNR-MICCAI BraTS 2021 challenge with their real-world partitioning
- CheXpert: A large dataset (over 100,000 images) of chest X-rays with uncertainty labels. Available demographical attributes: age, sex, and supplementary self-reported race.