Parallel Transport Convolution: A New Tool for Convolutional Neural Networks on Manifolds. - Stefan C. Schonsheck; Bin Dong; Rongjie Lai (CoRR, 2018)

Chart Auto-Encoders for Manifold Structured Data. - Stefan C. Schonsheck; Jie Chen 007; Rongjie Lai (CoRR, 2019)

Unsupervised Geometric Disentanglement for Surfaces via CFAN-VAE. - N. Joseph Tatro; Stefan C. Schonsheck; Rongjie Lai (CoRR, 2020)

Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning. - Stefan C. Schonsheck (CoRR, 2020)

Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit. - Stefan C. Schonsheck; Michael M. Bronstein; Rongjie Lai (J. Sci. Comput., 2021)

Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders. - Stefan C. Schonsheck; Scott Mahan; Timo Klock; Alexander Cloninger; Rongjie Lai (CoRR, 2022)

Parallel Transport Convolution: Deformable Convolutional Networks on Manifold-Structured Data. - Stefan C. Schonsheck; Bin Dong; Rongjie Lai (SIAM J. Imaging Sci., 2022)

Multiscale Transforms for Signals on Simplicial Complexes. - Naoki Saito 001; Stefan C. Schonsheck; Eugene Shvarts (CoRR, 2023)

Multiscale Hodge Scattering Networks for Data Analysis. - Naoki Saito 001; Stefan C. Schonsheck; Eugene Shvarts (CoRR, 2023)

Spherical coordinates from persistent cohomology. - Nikolas C. Schonsheck; Stefan C. Schonsheck (J. Appl. Comput. Topol., 2024)