Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. - Dhananjay Bhaskar; Kincaid MacDonald; Oluwadamilola Fasina; Dawson Thomas; Bastian Rieck; Ian Adelstein; Smita Krishnaswamy (NeurIPS, 2022)

Wire Before You Walk. - Tesfa Asmara; Dhananjay Bhaskar; Ian Adelstein; Smita Krishnaswamy; Michael Perlmutter (ACSSC, 2023)

Neural FIM for learning Fisher information metrics from point cloud data. - Oluwadamilola Fasina; Guillaume Huguet; Alexander Tong 001; Yanlei Zhang; Guy Wolf; Maximilian Nickel; Ian Adelstein; Smita Krishnaswamy (ICML, 2023)

A Flow Artist for High-Dimensional Cellular Data. - Kincaid MacDonald; Dhananjay Bhaskar; Guy Thampakkul; Nhi Nguyen; Joia Zhang; Michael Perlmutter; Ian Adelstein; Smita Krishnaswamy (MLSP, 2023)

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. - Guillaume Huguet; Alexander Tong 001; Edward De Brouwer; Yanlei Zhang; Guy Wolf; Ian Adelstein; Smita Krishnaswamy (NeurIPS, 2023)

BLIS-Net: Classifying and Analyzing Signals on Graphs. - Charles Xu 004; Laney Goldman; Valentina Guo; Benjamin Hollander-Bodie; Maedee Trank-Greene; Ian Adelstein; Edward De Brouwer; Rex Ying; Smita Krishnaswamy; Michael Perlmutter (AISTATS, 2024)

Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. - Danqi Liao; Chen Liu 020; Benjamin W. Christensen; Alexander Tong 001; Guillaume Huguet; Guy Wolf; Maximilian Nickel; Ian Adelstein; Smita Krishnaswamy (CISS, 2024)

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. - Xingzhi Sun 003; Danqi Liao; Kincaid MacDonald; Yanlei Zhang; Chen Liu 020; Guillaume Huguet; Guy Wolf; Ian Adelstein; Tim G. J. Rudner; Smita Krishnaswamy (CoRR, 2024)

Exploring the Manifold of Neural Networks Using Diffusion Geometry. - Elliott Abel; Peyton Crevasse; Yvan Grinspan; Selma Mazioud; Folu Ogundipe; Kristof Reimann; Ellie Schueler; Andrew J. Steindl; Ellen Zhang; Dhananjay Bhaskar; Siddharth Viswanath; Yanlei Zhang; et al. (CoRR, 2024)

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. - Xingzhi Sun 003; Danqi Liao; Kincaid MacDonald; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Ian Adelstein; Tim G. J. Rudner; Smita Krishnaswamy (AISTATS, 2025)

HiPoNet: A Topology-Preserving Multi-View Neural Network For High Dimensional Point Cloud and Single-Cell Data. - Siddharth Viswanath; Hiren Madhu; Dhananjay Bhaskar; Jake Kovalic; David R. Johnson; Rex Ying; Christopher J. Tape; Ian Adelstein; Michael Perlmutter; Smita Krishnaswamy (CoRR, 2025)