CMU Researchers Propose a Distributed Data Scoping Method: Revealing the Incompatibility between the Deep Learning Architecture and the Generic Transport PDEs

Generic transport equations, comprising time-dependent partial differential equations (PDEs), delineate the evolution of extensive properties in physical systems, encompassing mass, momentum, and energy. Derived from conservation laws, they underpin comprehension of diverse physical phenomena, from mass diffusion to Navier–Stokes equations. Widely applicable across science and engineering, these equations support high-fidelity simulations vital for addressing design […]

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