Differentiable Spline Approximations

no code implementations • NeurIPS 2021 • Minsu Cho, Aditya Balu, Ameya Joshi, Anjana Deva Prasad, Biswajit Khara, Soumik Sarkar, Baskar Ganapathysubramanian, Adarsh Krishnamurthy, Chinmay Hegde

Overall, we show that leveraging this redesigned Jacobian in the form of a differentiable "layer" in predictive models leads to improved performance in diverse applications such as image segmentation, 3D point cloud reconstruction, and finite element analysis.

3D Point Cloud Reconstruction BIG-bench Machine Learning +3

NURBS-Diff: A Differentiable Programming Module for NURBS

no code implementations • 29 Apr 2021 • Anjana Deva Prasad, Aditya Balu, Harshil Shah, Soumik Sarkar, Chinmay Hegde, Adarsh Krishnamurthy

These derivatives are used to define an approximate Jacobian used for performing the "backward" evaluation to train the deep learning models.

BIG-bench Machine Learning Point cloud reconstruction