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.
Global streamflow forecasting supports flood preparedness, yet data-driven models trained on reanalysis lose skill when driven by operational forecasts, increasingly so with lead time. AIFL addresses this shift with a two-stage transfer-learning recipe and a deterministic LSTM, but it feeds one forecast lead time into...
Rescene is presented, a 0.4 M-parameter wrapper around a frozen 1.5 degree, 6-hourly vision-transformer operator developed using ERA5 reanalysis data and comprising a deterministic"slow clock"(0.33 M) that blends the forecast toward a lead-aware day-of-year climatology and a generative head (0.06 M) that adds a spectra...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.