arxiv
PublishedSeptember 1, 2026 at 4:00 AM
Learning PDE Time-Stepping with Neural Cellular Automata
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arXiv:2608.30328v1 Announce Type: new Abstract: Classical numerical solvers for partial differential equations (PDEs) are computationally expensive to solve repeatedly across varying initial conditions, motivating the need for learned surrogates. In this paper, we propose a trainable Neural Cellular
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Originally published on arxiv ↗