Combining uniform manifold approximation with localized affine shadowsampling improves classification of imbalanced datasets. - Saptarshi Bej; Prashant Srivastava; Markus Wolfien; Olaf Wolkenhauer (IJCNN, 2021)

A Multi-Schematic Classifier-Independent Oversampling Approach for Imbalanced Datasets. - Saptarshi Bej; Kristian Schulz; Prashant Srivastava; Markus Wolfien; Olaf Wolkenhauer (IEEE Access, 2021)

Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling. - Saptarshi Bej; Anne-Marie Galow; Robert David; Markus Wolfien; Olaf Wolkenhauer (BMC Bioinform., 2021)

A multi-schematic classifier-independent oversampling approach for imbalanced datasets. - Saptarshi Bej; Kristian Schultz; Prashant Srivastava; Markus Wolfien; Olaf Wolkenhauer (CoRR, 2021)

LoRAS: an oversampling approach for imbalanced datasets. - Saptarshi Bej; Narek Davtyan; Markus Wolfien; Mariam Nassar; Olaf Wolkenhauer (Mach. Learn., 2021)

Improved imbalanced classification through convex space learning. - Saptarshi Bej (2021)

Attention Retrieval Model for Entity Relation Extraction From Biological Literature. - Prashant Srivastava; Saptarshi Bej; Kristian Schultz; Kristina Y. Yordanova; Olaf Wolkenhauer (IEEE Access, 2022)

Convex space learning improves deep-generative oversampling for tabular imbalanced classification on smaller datasets. - Kristian Schultz; Saptarshi Bej; Waldemar Hahn; Markus Wolfien; Prashant Srivastava; Olaf Wolkenhauer (CoRR, 2022)

Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing Data. - Rahul Bordoloi; Clémence Réda; Orell Trautmann; Saptarshi Bej; Olaf Wolkenhauer (CoRR, 2024)

Convex space learning for tabular synthetic data generation. - Manjunath Mahendra; Chaithra Umesh; Saptarshi Bej; Kristian Schultz; Olaf Wolkenhauer (CoRR, 2024)

ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. - Kristian Schultz; Saptarshi Bej; Waldemar Hahn; Markus Wolfien; Prashant Srivastava; Olaf Wolkenhauer (Pattern Recognit., 2024)

Bitter peptide prediction using graph neural networks. - Prashant Srivastava; Alexandra Steuer; Francesco Ferri; Alessandro Nicoli; Kristian Schultz; Saptarshi Bej; Antonella Di Pizio; Olaf Wolkenhauer (J. Cheminformatics, 2024)

Detection of pre-ictal epileptic events using a self-attention based neural network from raw Neonatal EEG data. - Kondaveeti Tejaswi; Madala Vikas; Himala Praharsha; Pranshu Mandal; Sujan Chakraborty; Olaf Wolkenhauer; Saptarshi Bej (Comput. Biol. Medicine, 2025)

Preserving logical and functional dependencies in synthetic tabular data. - Chaithra Umesh; Kristian Schultz; Manjunath Mahendra; Saptarshi Bej; Olaf Wolkenhauer (Pattern Recognit., 2025)

Fast Iterative and Task-Specific Imputation with Online Learning. - Rahul Bordoloi; Clémence Réda; Saptarshi Bej (CoRR, 2025)

Multivariate functional linear discriminant analysis for partially-observed time series. - Rahul Bordoloi; Clémence Réda; Orell Trautmann; Saptarshi Bej; Olaf Wolkenhauer (Mach. Learn., 2025)

Dependency-aware synthetic tabular data generation. - Chaithra Umesh; Kristian Schultz; Manjunath Mahendra; Saptarshi Bej; Olaf Wolkenhauer (CoRR, 2025)