Adelstein, Ian

8 publications

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

NeurIPS 2025 HiPoNet: A Multi-View Simplicial Complex Network for High Dimensional Point-Cloud and Single-Cell Data Siddharth Viswanath, Hiren Madhu, Dhananjay Bhaskar, Jake Kovalic, David R Johnson, Christopher Tape, Ian Adelstein, Rex Ying, Michael Perlmutter, Smita Krishnaswamy

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

ICMLW 2024 Geometry-Aware Autoencoders for Metric Learning and Generative Modeling on Data Manifolds Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy

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

ICMLW 2023 A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy

ICML 2023 Neural FIM for Learning Fisher Information Metrics from Point Cloud Data Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy

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