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cs.CV2025
NeuralDMD: Interpretable Neural Representation of Dynamics from Sparse and Noisy Measurements
Ali SaraerToosi, Renbo Tu, Kamyar Azizzadenesheli +2
Many challenges in scientific imaging involve solving ill-posed inverse problems, where the goal is to recover spatio-temporal fields from indirect, noisy, and highly sparse measur…
cs.CV2025
Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction
Chris Choy, Alexey Kamenev, Jean Kossaifi +3
Computational Fluid Dynamics (CFD) is crucial for automotive design, requiring the analysis of large 3D point clouds to study how vehicle geometry affects pressure fields and drag…