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NeuralDMD: Interpretable Neural Representation of Dynamics from Sparse and Noisy Measurements
Ali SaraerToosi, Renbo Tu, Esther Y. H. Lin +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…
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…
PaCMO: Partner Dependent Human Motion Generation in Dyadic Human Activity using Neural Operators
Md Ashiqur Rahman, Jasorsi Ghosh, Hrishikesh Viswanath +2
We address the problem of generating 3D human motions in dyadic activities. In contrast to the concurrent works, which mainly focus on generating the motion of a single actor from…