SCOPE trains a mask-conditioned student to predict the complete representation of a momentum teacher, with a shared decoder reconstructing fields from both predicted and full-view representations.
SCOPE recovers complete PDE fields from sparse observations via mask-conditioned latent prediction.
The authors pair mask-conditioned full-field latent prediction with a shared physical decoder, outperforming neural operators and diffusion-based solvers in ten evaluated tasks.
Academic
Ruichen Xu · Siyao Wang · Fang Wan · Jiacheng Qiu · Wenhan Gao · Jiaxing Zhang · +5 more
Stony Brook University · University of California, Davis · Independent Research · PayPal · New York University
Research Digest··2 min read
Thread:PDE Field Reconstruction
The authors propose SCOPE, a deterministic single-pass model that reconstructs complete PDE fields from sparse measurements by coupling full-target latent prediction with a shared physical decoder.
Why this paper
From Stony Brook University and 5 others
In one line
SCOPE recovers complete PDE fields from sparse observations using full-target latent prediction and shared physical reconstruction.
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