Kristian Schultz

According to our database, Kristian Schultz authored at least 8 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Dependency-aware synthetic tabular data generation.

Chaithra Umesh, Kristian Schultz, Manjunath Mahendra, Saptarshi Bej, Olaf Wolkenhauer

CoRR, July, 2025

Preserving logical and functional dependencies in synthetic tabular data.

Chaithra Umesh, Kristian Schultz, Manjunath Mahendra, Saptarshi Bej, Olaf Wolkenhauer

Pattern Recognit., 2025

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, December, 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., March, 2024

Convex space learning for tabular synthetic data generation.

Manjunath Mahendra, Chaithra Umesh, Saptarshi Bej, Kristian Schultz, Olaf Wolkenhauer

CoRR, 2024

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

Attention Retrieval Model for Entity Relation Extraction From Biological Literature.

Prashant Srivastava, Saptarshi Bej, Kristian Schultz, Kristina Y. Yordanova, Olaf Wolkenhauer

IEEE Access, 2022

2021

A multi-schematic classifier-independent oversampling approach for imbalanced datasets.

Saptarshi Bej, Kristian Schultz, Prashant Srivastava, Markus Wolfien, Olaf Wolkenhauer

CoRR, 2021