AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
2 papers indexed here
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.
This work proposes Compressed Active Subspaces (CAS), a scalable approach that first maps the model parameters to a compressed space using a structured isometric embedding and then constructs the active subspace within this reduced parameterization.
This work proposes a more sample-efficient data-augmentation strategy for generating NPDE training data from a computer model—specifically, one using an explicit, structured-grid finite-difference numerical solver—by space-filling sampling of local ‘stencil’ states.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.