[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库

NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).

[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架

Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.

[ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift

This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

1st place solution of RSNA Screening Mammography Breast Cancer Detection competition on Kaggle: https://www.kaggle.com/competitions/rsna-breast-cancer-detection

Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/

MICCAI 2023: DHC: Dual-debiased Heterogeneous Co-training Framework for Class-imbalanced Semi-supervised Medical Image Segmentation

ResLT: Residual Learning for Long-tailed Recognition (TPAMI 2022)

Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models

[ICLR 2023] Official Tensorflow implementation of "Distributionally Robust Post-hoc Classifiers under Prior Shifts"

(NeurIPS 2021) Realistic Evaluation of Transductive Few-Shot Learning

[ArXiv 2025] This repo is official PyTorch implementation of the paper "Learning Dense Hand Contact Estimation from Imbalanced Data".

[MICCAI2019 & TMI2020] Overfitting under Class Imbalance: Anaylsis and Improvements for Medical Image Segmentation.

[MICCAI'22] Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift

Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data