AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 2 of 5 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
The results show that exploiting paired anatomical correspondence enables diffusion-level LDCT reconstruction with a single step reconstruction, and across all REFM variants, one-step inference consistently provides the highest reconstruction quality.
B-MIM is introduced, a modification of the iBOT objective that stochastically reduces global semantic alignment to prioritize local patch reconstruction and suggests that reducing global semantic pressure during pretraining enhances generalization to intricate anatomical structures.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.