The following pages link to Testing the manifold hypothesis (Q5741444):
Displaying 39 items.
- Ricci curvature and the manifold learning problem (Q1631004) (← links)
- Metric thickenings of Euclidean submanifolds (Q1710638) (← links)
- Deep learning of thermodynamics-aware reduced-order models from data (Q2021918) (← links)
- Density estimation on an unknown submanifold (Q2044375) (← links)
- Robust \(k\)-means clustering for distributions with two moments (Q2054489) (← links)
- Dimensionality reduction for \(k\)-distance applied to persistent homology (Q2063202) (← links)
- Accelerating phase-field predictions via recurrent neural networks learning the microstructure evolution in latent space (Q2145130) (← links)
- Reconstruction and interpolation of manifolds. I: The geometric Whitney problem (Q2216248) (← links)
- On boundary detection (Q2227476) (← links)
- Interpolation, the rudimentary geometry of spaces of Lipschitz functions, and geometric complexity (Q2329040) (← links)
- Data analysis from empirical moments and the Christoffel function (Q2658553) (← links)
- Data-driven spatiotemporal modeling for structural dynamics on irregular domains by stochastic dependency neural estimation (Q2678544) (← links)
- Side effects of learning from low-dimensional data embedded in a Euclidean space (Q2687305) (← links)
- Computational mean-field games on manifolds (Q2699377) (← links)
- Occupants in manifolds (Q2979637) (← links)
- Reconstruction of a Riemannian Manifold from Noisy Intrinsic Distances (Q5037574) (← links)
- Inverse problems on low-dimensional manifolds (Q5061379) (← links)
- Geometric anomaly detection in data (Q5073125) (← links)
- A Metric Space for Point Process Excitations (Q5076362) (← links)
- Bayesian Imaging with Data-Driven Priors Encoded by Neural Networks (Q5094622) (← links)
- Model-Centric Data Manifold: The Data Through the Eyes of the Model (Q5094635) (← links)
- Persistent Intersection Homology for the Analysis of Discrete Data (Q5147727) (← links)
- Recovery of Surfaces and Functions in High Dimensions: Sampling Theory and Links to Neural Networks (Q5860295) (← links)
- IAN: Iterated Adaptive Neighborhoods for Manifold Learning and Dimensionality Estimation (Q5885248) (← links)
- Pursuit of a discriminative representation for multiple subspaces via sequential games (Q6099820) (← links)
- Universally consistent estimation of the reach (Q6101692) (← links)
- Deep nonparametric estimation of intrinsic data structures by chart autoencoders: generalization error and robustness (Q6144890) (← links)
- Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning (Q6171687) (← links)
- Deep nonparametric regression on approximate manifolds: nonasymptotic error bounds with polynomial prefactors (Q6172194) (← links)
- Applications of No-Collision Transportation Maps in Manifold Learning (Q6202282) (← links)
- Low dimensional approximation and generalization of multivariate functions on smooth manifolds using deep ReLU neural networks (Q6536393) (← links)
- Optimal 1-Wasserstein distance for WGANs (Q6589580) (← links)
- Tangent space and dimension estimation with the Wasserstein distance (Q6594420) (← links)
- Discretized gradient flow for manifold learning (Q6610080) (← links)
- Algebraic machine learning with an application to chemistry (Q6620120) (← links)
- Random Fixed Boundary Flows (Q6631731) (← links)
- Estimating a density near an unknown manifold: a Bayesian nonparametric approach (Q6656612) (← links)
- A Whitney extension problem for manifolds (Q6660794) (← links)
- Cartan moving frames and the data manifolds (Q6670444) (← links)
