Saptarshi Bej - RankMe

26 papers A* 1B 1Journal 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Anomaly Detection via Mean Shift Density Enhancement. CoRR Pritam Kar, Rahul Bordoloi, Olaf Wolkenhauer, Saptarshi Bej
2026	J	`jnl`	Convex space learning for tabular synthetic data generation. Neurocomputing Manjunath Mahendra, Chaithra Umesh, Kristian Schultz, Olaf Wolkenhauer, Saptarshi Bej
2026	J	`jnl`	Fast agreement-driven device-calibrated local learning paradigms for spiking neural networks. Neural Networks Saptarshi Bej, Muhammed Sahad E, Gouri Lakshmi, Harshit Kumar, Pritam Kar, Bikas C. Das
2026	A*	`conf`	Multivariate Functional Linear Discriminant Analysis for Partially-Observed Time Series (Abstract Reprint). AAAI Rahul Bordoloi, Clémence Réda, Orell Trautmann, Saptarshi Bej, Olaf Wolkenhauer
2026	J	`jnl`	Supervised Spike Agreement Dependent Plasticity for Fast Local Learning in Spiking Neural Networks. CoRR Gouri Lakshmi, Athira Chandrasekharan, Harshit Kumar, Muhammed Sahad E, Bikas C. Das, Saptarshi Bej
2025	J	`jnl`	Dependency-aware synthetic tabular data generation. CoRR Chaithra Umesh, Kristian Schultz, Manjunath Mahendra, Saptarshi Bej, Olaf Wolkenhauer
2025	J	`jnl`	Detection of pre-ictal epileptic events using a self-attention based neural network from raw Neonatal EEG data. Comput. Biol. Medicine Kondaveeti Tejaswi, Madala Vikas, Himala Praharsha, Pranshu Mandal, Sujan Chakraborty, Olaf Wolkenhauer, Saptarshi Bej
2025	J	`jnl`	FUSE: Fast Semi-Supervised Node Embedding Learning via Structural and Label-Aware Optimization. CoRR Sujan Chakraborty, Rahul Bordoloi, Anindya Sengupta, Olaf Wolkenhauer, Saptarshi Bej
2025	J	`jnl`	Fast Iterative and Task-Specific Imputation with Online Learning. CoRR Rahul Bordoloi, Clémence Réda, Saptarshi Bej
2025	J	`jnl`	Multivariate functional linear discriminant analysis for partially-observed time series. Mach. Learn. Rahul Bordoloi, Clémence Réda, Orell Trautmann, Saptarshi Bej, Olaf Wolkenhauer
2025	J	`jnl`	Preserving logical and functional dependencies in synthetic tabular data. Pattern Recognit. Chaithra Umesh, Kristian Schultz, Manjunath Mahendra, Saptarshi Bej, Olaf Wolkenhauer
2025	J	`jnl`	Spike Agreement Dependent Plasticity: A scalable Bio-Inspired learning paradigm for Spiking Neural Networks. CoRR Saptarshi Bej, Muhammed Sahad E, Gouri Lakshmi, Harshit Kumar, Pritam Kar, Bikas C. Das
2024	J	`jnl`	Bitter peptide prediction using graph neural networks. J. Cheminformatics Prashant Srivastava, Alexandra Steuer, Francesco Ferri, Alessandro Nicoli, Kristian Schultz, Saptarshi Bej, Antonella Di Pizio, Olaf Wolkenhauer
2024	J	`jnl`	ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. Pattern Recognit. Kristian Schultz, Saptarshi Bej, Waldemar Hahn, Markus Wolfien, Prashant Srivastava, Olaf Wolkenhauer
2024	J	`jnl`	Convex space learning for tabular synthetic data generation. CoRR Manjunath Mahendra, Chaithra Umesh, Saptarshi Bej, Kristian Schultz, Olaf Wolkenhauer
2024	J	`jnl`	Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing Data. CoRR Rahul Bordoloi, Clémence Réda, Orell Trautmann, Saptarshi Bej, Olaf Wolkenhauer
2024	J	`jnl`	Preserving logical and functional dependencies in synthetic tabular data. CoRR Chaithra Umesh, Kristian Schultz, Manjunath Mahendra, Saptarshi Bej, Olaf Wolkenhauer
2022	J	`jnl`	Attention Retrieval Model for Entity Relation Extraction From Biological Literature. IEEE Access Prashant Srivastava, Saptarshi Bej, Kristian Schultz, Kristina Y. Yordanova, Olaf Wolkenhauer
2022	J	`jnl`	Convex space learning improves deep-generative oversampling for tabular imbalanced classification on smaller datasets. CoRR Kristian Schultz, Saptarshi Bej, Waldemar Hahn, Markus Wolfien, Prashant Srivastava, Olaf Wolkenhauer
2021	J	`jnl`	A Multi-Schematic Classifier-Independent Oversampling Approach for Imbalanced Datasets. IEEE Access Saptarshi Bej, Kristian Schulz, Prashant Srivastava, Markus Wolfien, Olaf Wolkenhauer
2021	J	`jnl`	A multi-schematic classifier-independent oversampling approach for imbalanced datasets. CoRR Saptarshi Bej, Kristian Schultz, Prashant Srivastava, Markus Wolfien, Olaf Wolkenhauer
2021	J	`jnl`	Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling. BMC Bioinform. Saptarshi Bej, Anne-Marie Galow, Robert David, Markus Wolfien, Olaf Wolkenhauer
2021	B	`conf`	Combining uniform manifold approximation with localized affine shadowsampling improves classification of imbalanced datasets. IJCNN Saptarshi Bej, Prashant Srivastava, Markus Wolfien, Olaf Wolkenhauer
2021	—	`—`	Improved imbalanced classification through convex space learning. Saptarshi Bej
2021	J	`jnl`	LoRAS: an oversampling approach for imbalanced datasets. Mach. Learn. Saptarshi Bej, Narek Davtyan, Markus Wolfien, Mariam Nassar, Olaf Wolkenhauer
2019	J	`jnl`	LoRAS: An oversampling approach for imbalanced datasets. CoRR Saptarshi Bej, Narek Davtyan, Markus Wolfien, Mariam Nassar, Olaf Wolkenhauer