most citedOperator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions

7 citations · 11 across the 3 of their papers we have counts for

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cs.LG2024★ 4 cited

TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence Generation

Lin Zongying, Li Hao, Lv Liuzhenghao +5

Designing protein sequences with specific biological functions and structural stability is crucial in biology and chemistry. Generative models already demonstrated their capabiliti…

cs.LG2023★ 7 cited

Operator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions

Bin Lin, Zhiping Mao, Zhicheng Wang +1

Physics-informed Neural Networks (PINNs) have been shown as a promising approach for solving both forward and inverse problems of partial differential equations (PDEs). Meanwhile,…