Work

Data Augmentation with Variational Autoencoder for Imbalanced Dataset

Year: 2024

Type: other

Abstract: Our paper, Data Augmentation with Variational Autoencoder for Imbalanced Dataset, with Samuel Stocksieker and Denys Pommeret is now online on ArXiv. Learning from an imbalanced distribution presents a major challenge in predictive modeling, as it generally leads to a reduction in the performance of standard algorithms. Various approaches exist to address this issue, but many of them concern classification problems, with a limited focus on regression. In this paper, we introduce a novel metho...

Source: Industrias Culturais (Universidade de Coimbra)

DOI: 10.58079/12woq

Author: Arthur Charpentier

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6917633445

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