1 citations · 1 across the 10 of their papers we have counts for
12 papers
HarmoCore: Functional Latent Diffusion for Sparse Reconstruction of Oscillatory Wave Fields
Lihao Chen, Xinyu Zhang, Panqi Chen +4
Reconstructing oscillatory wave fields from scattered sensors is a severely underdetermined inverse problem. Beyond the challenges of general physical-field reconstruction, wave re…
TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing
Xinyu Zhang, Lihao Chen, Panqi Chen +4
Reconstructing continuous physical fields from sparse measurements is central to scientific monitoring, inverse modeling, and digital-twin construction. Generative reconstruction h…
Mitigating Spectral Bias in Neural Operators for Underwater Transmission Loss Prediction
Yifan Sun, Shikai Fang, Chao Zhang +3
Predicting underwater acoustic transmission loss rapidly and accurately is crucial for real-time ocean acoustic applications. While Fourier Neural Operators (FNO) have emerged as p…
Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation
Jiawei Chen, Xiaofan Gui, Shikai Fang +4
Parameterizing high-fidelity "digital twins" of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Prevailing methods formulate th…
APEX: Amplitude Anchors and Phase Priors for Target-Scarce Higher-Frequency Wave Prediction
Yifan Sun, Lei Cheng, Sijie Chen +3
Learning-based surrogates have become increasingly effective for wave-field prediction, and neural operators in particular have shown strong performance within observed frequency r…
StreamPhy: Streaming Inference of High-Dimensional Physical Dynamics via State Space Models
Panqi Chen, Yifan Sun, Shikai Fang +2
Inferring the evolution of high-dimensional and multi-modal (e.g., spatio-temporal) physical fields from irregular sparse measurements in real time is a fundamental challenge in sc…