Intrinsic Dimension Estimation Using Wasserstein Distances

Intrinsic Dimension Estimation Using Wasserstein Distances

8 June 2021

Yury Polyanskiy

Alexander Rakhlin

Papers citing "Intrinsic Dimension Estimation Using Wasserstein Distances"

19 / 19 papers shown

Title
Deep Generative Models: Complexity, Dimensionality, and Approximation Kevin Wang Hongqian Niu Yixin Wang Didong Li DRL 41 0 0 01 Apr 2025
Is Smoothness the Key to Robustness? A Comparison of Attention and Convolution Models Using a Novel Metric Baiyuan Chen MLT 28 0 0 23 Oct 2024
Integrating Natural Language Prompting Tasks in Introductory Programming Courses Chris Kerslake Paul Denny David H Smith IV James Prather Juho Leinonen Andrew Luxton-Reilly Stephen MacNeil 31 1 0 04 Oct 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds Hong Ye Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 57 0 0 13 Aug 2024
Statistical inference of convex order by Wasserstein projection Jakwang Kim Young-Heon Kim Yuanlong Ruan Andrew Warren 39 2 0 05 Jun 2024
Beyond the noise: intrinsic dimension estimation with optimal neighbourhood identification A. Di Noia Iuri Macocco Aldo Glielmo A. Laio Antonietta Mira 48 3 0 24 May 2024
Generative adversarial learning with optimal input dimension and its adaptive generator architecture Zhiyao Tan Ling Zhou Huazhen Lin GAN 42 0 0 06 May 2024
Bayesian one- and two-sided inference on the local effective dimension Eduard Belitser 14 0 0 29 Jan 2024
Manifold learning: what, how, and why M. Meilă Hanyu Zhang 17 55 0 07 Nov 2023
Sample Complexity Bounds for Estimating Probability Divergences under Invariances B. Tahmasebi Stefanie Jegelka 54 6 0 06 Nov 2023
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature Anna C. Gilbert Kevin OÑeill 22 0 0 23 Sep 2023
Manifold Regularization for Memory-Efficient Training of Deep Neural Networks Shadi Sartipi Edgar A. Bernal 22 0 0 26 May 2023
A statistical framework for analyzing shape in a time series of random geometric objects Anne van Delft Andrew J. Blumberg 13 2 0 04 Apr 2023
Data-Copying in Generative Models: A Formal Framework Robi Bhattacharjee S. Dasgupta Kamalika Chaudhuri TDI 20 6 0 25 Feb 2023
Relating Regularization and Generalization through the Intrinsic Dimension of Activations Bradley Brown Jordan Juravsky Anthony L. Caterini G. Loaiza-Ganem 33 3 0 23 Nov 2022
Discovering Conservation Laws using Optimal Transport and Manifold Learning Peter Y. Lu Rumen Dangovski M. Soljavcić 27 17 0 31 Aug 2022
Statistical guarantees for generative models without domination Nicolas Schreuder Victor-Emmanuel Brunel A. Dalalyan GAN 65 34 0 19 Oct 2020
Minimax Rates for Estimating the Dimension of a Manifold Jisu Kim Alessandro Rinaldo Larry A. Wasserman 166 24 0 03 May 2016
Adaptive Metric Dimensionality Reduction Lee-Ad Gottlieb A. Kontorovich Robert Krauthgamer 56 38 0 12 Feb 2013