A novel FlowViT-Diff framework that integrates a Vision Transformer (ViT) with an enhanced denoising diffusion probabilistic model (DDPM) for super-resolution reconstruction of high-resolution flow ...

A new research model called PiGRAND merges physics guidance with graph neural diffusion to predict and control AM processes.

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as ...

Generative Adversarial Networks (GANs) are a class of deep learning models that learn to produce new (or pseudo-real) data. Their advent in 2014 and refinement thereafter have led to them dominating ...

Diffusion models gradually refine and produce a requested output, sometimes starting from random noise—values generated by the model itself—and sometimes working from user-provided data. Think of ...