manifold hypothesis

A Geometric Framework for Understanding Memorization in Generative Models ICLR 2025 Deep Generative Models: Complexity, Dimensionality, and Approximation JMLR 2025 Linear Convergence of Diffusion Models Under the Manifold Hypothesis COLT 2025 Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion ICLR 2025 Optimal Denoising in Score-Based Generative Models: The Role of Data Regularity JMLR 2025 Adversarial Purification with the Manifold Hypothesis AAAI 2024 CW Complex Hypothesis for Image Data ICML 2024 Hardness of Learning Neural Networks under the Manifold Hypothesis NeurIPS 2024 Manifold Preserving Guided Diffusion ICLR 2024 State Representation Learning Using an Unbalanced Atlas ICLR 2024 Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data NeurIPS 2024 Implicit Manifold Gaussian Process Regression NeurIPS 2023 Topological Singularity Detection at Multiple Scales ICML 2023 Verifying the Union of Manifolds Hypothesis for Image Data ICLR 2023 Intrinsic Dimension Estimation Using Wasserstein Distance JMLR 2022 On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds NeurIPS 2022 Topology of Word Embeddings: Singularities Reflect Polysemy COLING 2020