😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切:论文、代码、框架与库
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Updated
Apr 26, 2024
😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切:论文、代码、框架与库
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
[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
Code repository for the online course Machine Learning with Imbalanced Data
[NeurIPS 2020] Balanced Meta-Softmax for Long-Tailed Visual Recognition
[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
This is the official PyTorch implementation of the paper "Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning" (Ju He, Adam Kortylewski, Shaokang Yang, Shuai Liu, Cheng Yang, Changhu Wang, Alan Yuille).
Implementation code of RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data accepted by Medical Image Analysis Journal (MedIA 2022)
Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction"
This is a multiclass classification project to classify severity of road accidents into three categories. this project is based on real-world data and dataset is also highly imbalanced.
DGSSC: A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspectral Imagery, TCSVT, 2022
A collection of Open Source Contributions in Learning from Imbalanced and Overlapped Data
(EMNLP 2023 Findings) Text2Tree: Aligning Text Representation to the Label Tree Hierarchy for Imbalanced Medical Classification.
Many algorithms for imbalanced data support binary and multiclass classification only. This approach is made for mulit-label classification (aka multi-target classification). 🌻
Learning Imbalanced Datasets With Maximum Margin Losss
DuBE: Duple-balanced Ensemble Learning from Skewed Data
Predictors for Blood-Brain Barrier Permeability with resampling strategies based on B3DB database.
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