Author

Shikai Fang

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Preprint Aug 2026

Mitigating Spectral Bias in Neural Operators for Underwater Transmission Loss Prediction

Predicting underwater acoustic transmission loss rapidly and accurately is crucial for real-time ocean acoustic applications. While Fourier Neural Operators (FNO) have emerged as powerful surrogate models due to their global receptive fields, they suffer from spectral bias. The frequency truncation mechanism in FNO fil...

Yifan Sun, Shikai Fang, Chao Zhang et al. · 0 citations

Preprint Aug 2026

TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing

Reconstructing continuous physical fields from sparse measurements is central to scientific monitoring, inverse modeling, and digital-twin construction. Generative reconstruction has recently emerged as a promising paradigm for this task by learning data-driven physical priors that complete plausible full fields from l...

Xin-Yu Zhang, Li-Hao Chen, Panqi Chen et al. · 0 citations

#machine learning Preprint Sep 2026

HarmoCore: Functional Latent Diffusion for Sparse Reconstruction of Oscillatory Wave Fields

HarmoCore is proposed, which places a generative prior in a compact, continuous, and structured wave-field latent, and learns a frequency-conditioned core diffusion prior, and performs Diffusion Posterior Sampling directly in core space.

Li-Hao Chen, Xin-Yu Zhang, Panqi Chen et al. · 0 citations