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cs.CV2026
Manifold Navigation Learning Using Recurrent Networks: Efficient Training Techniques
Sarah Harkins Dayton, Sathya Rengaswami, Vasileios Maroulas +2
Position tracking is a well-studied problem in Euclidean navigation, yet comparatively little attention has been given to navigation on general manifolds, where motion is governed…
nlin.AO2026
Complexity synchronization as a diagnostic and control principle for adaptive systems
Korosh Mahmoodi, Scott E. Kerick, Piotr J. Franaszczuk +3
Adaptive systems can exhibit similar levels of performance while relying on fundamentally different internal modes of coordination. Standard metrics such as average cooperation or…
cs.LG2026
From Classical to Topological Neural Networks Under Uncertainty
Sarah Harkins Dayton, Layal Bou Hamdan, Ioannis D. Schizas +2
This chapter explores neural networks, topological data analysis, and topological deep learning techniques, alongside statistical Bayesian methods, for processing images, time seri…