Bidirectional Normalizing Flow: From Data to Noise and Back
Published:Dec 11, 2025 18:59
•1 min read
•ArXiv
Analysis
This article likely discusses a novel approach in machine learning, specifically focusing on normalizing flows. The bidirectional aspect suggests the model can transform data into noise and reconstruct data from noise, potentially improving generative modeling or anomaly detection capabilities. The source, ArXiv, indicates this is a research paper.
Key Takeaways
- •Focuses on bidirectional normalizing flows.
- •Likely related to generative modeling or anomaly detection.
- •Based on a research paper.
Reference
“”