Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

The method reinterpreted Schrödinger bridge models as variational autoencoders with infinitely many latent variables, reducing computational costs and preventing overfitting. By appropriately ...

Advancements in whole-genome sequencing have revolutionized plant species characterization, providing a wealth of genotypic data for analysis. The combination of genomic selection and neural networks, ...

The key challenge in credit card fraud detection lies in the imbalance between legitimate and fraudulent transactions. Fraud ...