AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 3 of 47 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.
Generative models make molecular crystal structure prediction fast, but their samples still exhibit geometric and packing violations. Physics can be introduced during training, post-training, or inference, yet these choices are rarely compared with the generator and physical signal held fixed. We introduce CrystAF, an...
Existing protein geometry models typically represent molecular surfaces using local geometric features such as sampled points, normals, and curvature. While effective for capturing exposed molecular shape, these representations do not explicitly model the volumetric organization beneath the surface or provide a consist...
Boltz2ESI is introduced, an end-to-end framework that predicts enzyme–substrate interactions by leveraging structural knowledge learned by a biomolecular foundation model and consistently outperforms state-of-the-art sequence-based and rigid-docking approaches.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.