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Prashant Srivastava
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2020 – today
- 2024
- [j4]Prashant Srivastava, Alexandra Steuer, Francesco Ferri, Alessandro Nicoli, Kristian Schultz, Saptarshi Bej, Antonella Di Pizio, Olaf Wolkenhauer:
Bitter peptide prediction using graph neural networks. J. Cheminformatics 16(1): 111 (2024) - [j3]Kristian Schultz, Saptarshi Bej
, Waldemar Hahn, Markus Wolfien
ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. Pattern Recognit. 147: 110138 (2024) - 2022
- [j2]Prashant Srivastava
Attention Retrieval Model for Entity Relation Extraction From Biological Literature. IEEE Access 10: 22429-22440 (2022) - [i2]Kristian Schultz, Saptarshi Bej, Waldemar Hahn, Markus Wolfien, Prashant Srivastava, Olaf Wolkenhauer:
Convex space learning improves deep-generative oversampling for tabular imbalanced classification on smaller datasets. CoRR abs/2206.09812 (2022) - 2021
- [j1]Saptarshi Bej, Kristian Schulz, Prashant Srivastava
A Multi-Schematic Classifier-Independent Oversampling Approach for Imbalanced Datasets. IEEE Access 9: 123358-123374 (2021) - [c2]Saptarshi Bej, Prashant Srivastava, Markus Wolfien
Combining uniform manifold approximation with localized affine shadowsampling improves classification of imbalanced datasets. IJCNN 2021: 1-8 - [i1]Saptarshi Bej, Kristian Schultz, Prashant Srivastava, Markus Wolfien, Olaf Wolkenhauer:
A multi-schematic classifier-independent oversampling approach for imbalanced datasets. CoRR abs/2107.07349 (2021)
2000 – 2009
- 2009
- [c1]Vivek Kumar Sehgal, Rohit Sharma, Nitin, Deepankar Bhardwaj, Yaras Agarwal, Mehboob Shrivastava, Prashant Srivastava, Avinash Kumar:
D-Torus Topology in Networks-on-Chip: A Perspective Study. ESA 2009: 163-168
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