AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 2 of 26 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.
SplitJEPA is introduced, a JEPA that jointly recovers the latent state and its invariant and variant organization directly in representation space, without any reconstruction, and extends reconstruction-free latent recovery to invariant-variant block identification.
TSR consistently improves forward transfer while maintaining stability, outperforming existing replay baselines across heterogeneous and homogeneous task streams and argues for treating transfer as a first-class objective of continual learning, to be understood before it is engineered.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.