We are still trying to solve exponential problems with linear instincts. As megatrends converge over the next five to 10 years, they will render the old playbook obsolete.

If the receiver of an anonymous message is taken to be the adversary, then their best guess from a set of candidate senders ...

The proposed framework consists of a learning module named Learning Graph Dynamics with External Contact for deformable linear objects (LG-DEC) and an action generation module. The LG-DEC uses a graph ...

In this paper, we propose a versatile graph inference framework for learning from graph signals corrupted by exponential family noise. Our framework generalizes previous methods from continuous smooth ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

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