A robust framework for generating physically plausable vector fields using diffusion models and physics-informed guidance.
Enforce physical constraints like incompressibility (zero divergence) and irrotationality (zero curl) during sampling.
Generate dense vector fields from sparse streamline inputs using advanced diffusion techniques.
Built-in Gradio interface for training models, visualizing datasets, and running inference in real-time.