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Found 3 papers, 1 papers with code
Towards General-Purpose Representation Learning of Polygonal Geometries
For the spatial domain approach, we propose ResNet1D, a 1D CNN-based polygon encoder, which uses circular padding to achieve loop origin invariance on simple polygons.
Leveraging Bayesian Analysis To Improve Accuracy of Approximate Models
We focus on improving the accuracy of an approximate model of a multiscale dynamical system that uses a set of parameter-dependent terms to account for the effects of unresolved or neglected dynamics on resolved scales.
ShapeFlow: Learnable Deformation Flows Among 3D Shapes
Such a space naturally allows the disentanglement of geometric style (coming from the source) and structural pose (conforming to the target).
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