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cs.LG2026
Learning Incompressible 3D Flows from Sparse Samples: A Set Transformer Approach to Divergence-Free Kernel Fitting
Ramzi Idoughi, Radouan Boukharfane, Peter Wonka
Recovering divergence-free velocity fields from sparse and corrupted observations requires reconciling physical consistency, expressive representations, and robustness to missing d…
cs.LG2024★ 1 cited
HDNet: Physics-Inspired Neural Network for Flow Estimation based on Helmholtz Decomposition
Miao Qi, Ramzi Idoughi, Wolfgang Heidrich
Flow estimation problems are ubiquitous in scientific imaging. Often, the underlying flows are subject to physical constraints that can be exploited in the flow estimation; for exa…