2 papers
eess.SP2025
FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator
Vitalii Bondar, Serhii Semenov, Vira Babenko +1
Synthetic electrocardiogram generation serves medical AI applications requiring privacy-preserving data sharing and training dataset augmentation. Current diffusion-based methods a…
cs.LG2025
Deep generative models as the probability transformation functions
Vitalii Bondar, Vira Babenko, Roman Trembovetskyi +2
This paper introduces a unified theoretical perspective that views deep generative models as probability transformation functions. Despite the apparent differences in architecture…