D-Torus Topology in Networks-on-Chip: A Perspective Study. - Vivek Kumar Sehgal; Rohit Sharma 001; Nitin 001; Deepankar Bhardwaj; Yaras Agarwal; Mehboob Shrivastava; Prashant Srivastava; Avinash Kumar 002 (ESA, 2009)

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)

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

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)