← Search

Yuan Mi

2 accepted papers

2026

PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Burst-Sampled Spatiotemporal Dynamics

AAAI 2026technical

Deep learning has shown strong potential in modeling complex spatiotemporal dynamics. However, most existing methods depend on densely and uniformly sampled data, which is often unavailable in practice due to sensor and cost limitations. In many real-world settings, such as mobile sensing and physic

Cited by 0SourcePDFScholar
2025

MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation

ICML 2025poster

Solving partial differential equations (PDEs) by numerical methods meet computational cost challenge for getting the accurate solution since fine grids and small time steps are required. Machine learning can accelerate this process, but struggle with weak generalizability, interpretability, and data…

Cited by 0SourcePDFScholar