low-dimensional manifold

AIM: Manifold-based Data Filtering for Representation Finetuning AAAI 2026 Mapping Networks CVPR 2026 Category-Agnostic Neural Object Rigging CVPR 2025 Exploring Topological Properties in Artificial Neural Networks AAAI 2025 Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models NeurIPS 2024 Graph Mixup on Approximate Gromov–Wasserstein Geodesics ICML 2024 Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks NeurIPS 2024 Reconstructing the Geometry of Random Geometric Graphs (Extended Abstract) COLT 2024 Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds JMLR 2024 Spherical Rotation Dimension Reduction with Geometric Loss Functions JMLR 2024 Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data NeurIPS 2024 A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models JMLR 2023 Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks ICLR 2023 A composable machine-learning approach for steady-state simulations on high-resolution grids NeurIPS 2022 Isotropy in the Contextual Embedding Space: Clusters and Manifolds ICLR 2021 DROCC: Deep Robust One-Class Classification ICML 2020 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds NeurIPS 2019 Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks NeurIPS 2018 The K-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates ALT 2018 Manifold Based Dynamic Texture Synthesis from Extremely Few Samples CVPR 2014 Locally Linear Denoising on Image Manifolds AISTATS 2010