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Xinhai Chen

3 accepted papers

2026

Learning to Generate Structured Meshes with In-Context: Toward Generalization in Mesh Generation

AAAI 2026technical

Structured mesh generation serves as a crucial preprocessing step in numerical simulations and can be formulated as a mapping problem from geometry to structured mesh. Existing approaches typically establish an isolated mapping for each geometry. This geometry-specific paradigm fails to capture and

Cited by 0SourcePDFScholar
2025

PEINR: A Physics-enhanced Implicit Neural Representation for High-Fidelity Flow Field Reconstruction

ICML 2025poster

Implicit neural representation (INR) has now been thrust into the limelight with its flexibility in high-fidelity flow field reconstruction tasks. However, the lack of standard benchmarking datasets and the grid independence assumption for INR-based methods hinder progress and adoption in real-world…

Cited by 0SourcePDFScholar
2025

UGM2N: An Unsupervised and Generalizable Mesh Movement Network via M-Uniform Loss

NeurIPS 2025poster

Partial differential equations (PDEs) form the mathematical foundation for modeling physical systems in science and engineering, where numerical solutions demand rigorous accuracy-efficiency tradeoffs. Mesh movement techniques address this challenge by dynamically relocating mesh nodes to rapidly-va…

Cited by 0SourceScholar