AI RESEARCH
Biomimetic PINNs for Cell-Induced Phase Transitions: UQ-R3 Sampling with Causal Gating
arXiv CS.LG
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ArXi:2603.29184v1 Announce Type: new Nonconvex multi-well energies in cell-induced phase transitions give rise to sharp interfaces, fine-scale microstructures, and distance-dependent inter-cell coupling, all of which pose significant challenges for physics-informed learning. Existing methods often suffer from over-smoothing in near-field patterns. To address this, we propose biomimetic physics-informed neural networks (Bio-PINNs), a variational framework that encodes temporal causality into explicit spatial causality via a progressive distance gate.