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Data Augmentation for Imbalanced Regression

Data Augmentation for Imbalanced Regression

International Conference on Artificial Intelligence and Statistics (AISTATS), 2023

18 February 2023

Samuel Stocksieker

Arthur Charpentier

ArXiv (abs)PDF HTML Github

Papers citing "Data Augmentation for Imbalanced Regression"

6 / 6 papers shown

Local distribution-based adaptive oversampling for imbalanced regression

Local distribution-based adaptive oversampling for imbalanced regression

Shayan Alahyari

Mike Domaratzki

236

2

0

19 Apr 2025

Data Augmentation with Variational Autoencoder for Imbalanced Dataset

Data Augmentation with Variational Autoencoder for Imbalanced DatasetInternational Conference on Neural Information Processing (ICONIP), 2024

Samuel Stocksieker

Arthur Charpentier

327

6

0

09 Dec 2024

Review of Data-centric Time Series Analysis from Sample, Feature, and
Period

Review of Data-centric Time Series Analysis from Sample, Feature, and Period

256

2

0

24 Apr 2024

Boarding for ISS: Imbalanced Self-Supervised: Discovery of a Scaled
Autoencoder for Mixed Tabular Datasets

Boarding for ISS: Imbalanced Self-Supervised: Discovery of a Scaled Autoencoder for Mixed Tabular DatasetsIEEE International Joint Conference on Neural Network (IJCNN), 2024

Samuel Stocksieker

Arthur Charpentier

274

2

0

23 Mar 2024

Generalized Oversampling for Learning from Imbalanced datasets and
Associated Theory

Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory

Samuel Stocksieker

Arthur Charpentier

253

3

0

05 Aug 2023

$Few-shot $\mathbf{1/a}$ Anomalies Feedback : Damage Vision Mining Opportunity and Embedding Feature Imbalance$

\mathbf{1/a}

Anomalies Feedback : Damage Vision Mining Opportunity and Embedding Feature Imbalance

713

0

0

24 Jul 2023

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