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An "augmentation-free" rotation invariant classification scheme on point-cloud and its application to neuroimaging
Liu Yang, Rudrasis Chakraborty
Recent years have witnessed the emergence and increasing popularity of 3D medical imaging techniques with the development of 3D sensors and technology. However, achieving geometric…
A GMM based algorithm to generate point-cloud and its application to neuroimaging
Liu Yang, Rudrasis Chakraborty
Recent years have witnessed the emergence of 3D medical imaging techniques with the development of 3D sensors and technology. Due to the presence of noise in image acquisition, reg…
POIRot: A rotation invariant omni-directional pointnet
Liu Yang, Rudrasis Chakraborty, Stella X. Yu
Point-cloud is an efficient way to represent 3D world. Analysis of point-cloud deals with understanding the underlying 3D geometric structure. But due to the lack of smooth topolog…
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs
Liu Yang, Sean Treichler, Thorsten Kurth +8
Uncertainty quantification for forward and inverse problems is a central challenge across physical and biomedical disciplines. We address this challenge for the problem of modeling…
Potential Flow Generator with Optimal Transport Regularity for Generative Models
Liu Yang, George Em Karniadakis
We propose a potential flow generator with optimal transport regularity, which can be easily integrated into a wide range of generative models including different versions of…