arXiv Machine Learning June 2, 2026 By Tong Wu, Andrew Campbell, Anna Scaglione

Graph Transfer Learning via Shared Latent Geometry: Theory and Applications

Read the original on arXiv Machine Learning →

arXiv:2606. 00716v1 Announce Type: new Abstract: Inference and control in engineered physical systems pay a heavy physics cost at deployment: state estimators, inverse-problem solvers, model-predictive controllers, schedulers, and observers are often not closed-form and must re-solve a numerical optimization per instance, with the operator re-supplied each time.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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