Cover Image

Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Diepeveen, Willem, Leong, Oscar
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Differential Geometry Optimization and Control Statistics Theory 62R30, 65K10, 65J22, 68T07, 53Z50
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Iso-Riemannian Optimization on Learned Data Manifolds
by: Diepeveen, Willem, et al.
Published: (2025)

Retraction based regression methods on Riemannian manifolds
by: Loayza-Romero, Estefanía, et al.
Published: (2026)

Autoregressive Processes on Stiefel and Grassmann Manifolds
by: Figueras, Jordi-Lluís, et al.
Published: (2025)

Pulling back symmetric Riemannian geometry for data analysis
by: Diepeveen, Willem
Published: (2024)

TED++: Submanifold-Aware Backdoor Detection via Layerwise Tubular-Neighbourhood Screening
by: Le, Nam, et al.
Published: (2025)

LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters
by: Bogachev, Vladimir, et al.
Published: (2025)

Generalizing Adam to Manifolds for Efficiently Training Transformers
by: Brantner, Benedikt
Published: (2023)

Data Completion for Electrical Impedance Tomography by Conditional Diffusion Models
by: Chen, Ke, et al.
Published: (2026)

Bi-invariant Dissimilarity Measures for Sample Distributions in Lie Groups
by: Hanik, Martin, et al.
Published: (2024)

On empirical Hodge Laplacians under the manifold hypothesis
by: Lerch, Jan-Paul, et al.
Published: (2025)

A Survey of Dimension Estimation Methods
by: Binnie, James A. D., et al.
Published: (2025)

ConicCurv: A curvature estimation algorithm for planar polygons
by: Fuentes, R. Díaz, et al.
Published: (2025)

Towards optimal sensor placement for inverse problems in spaces of measures
by: Huynh, Phuoc-Truong, et al.
Published: (2023)

Curvature-driven manifold fitting under unbounded isotropic noise
by: Li, Ruowei, et al.
Published: (2026)

Extended Kalman Filtering on Stiefel Manifolds
by: Figueras, Jordi-Lluís, et al.
Published: (2025)

Learning where to learn: Training data distribution optimization for scientific machine learning
by: Guerra, Nicolas, et al.
Published: (2025)

On the Gaussian Kinematic Formula of R. Adler and J. Taylor
by: Fu, Joseph H. G.
Published: (2024)

Intrinsic-Metric Physics-Informed Neural Networks (IM-PINN) for Reaction-Diffusion Dynamics on Complex Riemannian Manifolds
by: Chrisnanto, Julian Evan, et al.
Published: (2025)

Manifold learning in Wasserstein space
by: Hamm, Keaton, et al.
Published: (2023)

MAGNET: an open-source library for mesh agglomeration by Graph Neural Networks
by: Antonietti, Paola F., et al.
Published: (2025)

Characterization of geodesic completeness for landmark space
by: Habermann, Karen, et al.
Published: (2025)

Curvature Corrected Nonnegative Manifold Data Factorization
by: Chew, Joyce, et al.
Published: (2025)

Recovery of a matrix valued potential for the wave equation on stationary spacetimes
by: Filippas, Spyridon, et al.
Published: (2025)

A new sparsity promoting residual transform operator for Lasso regression
by: Xiao, Yao, et al.
Published: (2025)

On the Convergence of the Extended Kalman Filter on Stiefel Manifolds when Observing a Constant Particle with Measurement Errors
by: Figueras, Jordi-Lluís, et al.
Published: (2025)

A global optimum-informed greedy algorithm for A-optimal experimental design
by: Aarset, Christian
Published: (2024)

Long-time existence of Brownian motion on configurations of two landmarks
by: Habermann, Karen, et al.
Published: (2023)

Convergence of Riemannian Stochastic Gradient Descents: Varying Batch Sizes And Nonstandard Batch Forming
by: Wu, Hao
Published: (2026)

Score matching for sub-Riemannian bridge sampling
by: Grong, Erlend, et al.
Published: (2024)

Free-Boundary Quasiconformal Maps via a Least-squares Operator in Diffeomorphism Optimization
by: Xu, Zhehao, et al.
Published: (2025)

Achieving Universal Approximation and Universal Interpolation via Nonlinearity of Control Families
by: Cai, Yongqiang, et al.
Published: (2025)

A Riemannian quasi-Newton algorithm for optimization with Euclidean bounds
by: Baran, Mateusz, et al.
Published: (2026)

Accelerating Newton-Schulz Iteration for Orthogonalization via Chebyshev-type Polynomials
by: Grishina, Ekaterina, et al.
Published: (2025)

On the approximation of the Riemannian barycenter
by: Mataigne, Simon, et al.
Published: (2025)

Self-adaptive physics-informed neural network for forward and inverse problems in heterogeneous porous flow
by: Aziz, Md. Abdul, et al.
Published: (2025)

A Numerical PDEs Approach to Evolution Equations in Shape Analysis Based on Regularized Morphoelasticity
by: Zhou, Ziqin
Published: (2026)

Fast $k$-means clustering in Riemannian manifolds via Fréchet maps: Applications to large-dimensional SPD matrices
by: Shi, Ji, et al.
Published: (2025)

The Neural Approximated Virtual Element Method for Elasticity Problems
by: Berrone, Stefano, et al.
Published: (2025)

Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data
by: Gyger, Tim, et al.
Published: (2024)

Sensitivity of low-rank matrix recovery
by: Breiding, Paul, et al.
Published: (2021)