Saved in:
| Main Author: | Khilar, Snigdha Chandan |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.30836 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Continual Learning as a Multiphase Moving-Boundary Problem
by: Khilar, Snigdha Chandan
Published: (2026)
by: Khilar, Snigdha Chandan
Published: (2026)
PFlow-T: A Persistence-Driven Forward Process for Topology-Controlled Generation
by: Khilar, Snigdha Chandan
Published: (2026)
by: Khilar, Snigdha Chandan
Published: (2026)
A singular Riemannian Geometry Approach to Deep Neural Networks III. Piecewise Differentiable Layers and Random Walks on $n$-dimensional Classes
by: Benfenati, Alessandro, et al.
Published: (2024)
by: Benfenati, Alessandro, et al.
Published: (2024)
On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization
by: Shumaylov, Zakhar, et al.
Published: (2025)
by: Shumaylov, Zakhar, et al.
Published: (2025)
Continuum Limits of Ollivier's Ricci Curvature on data clouds: pointwise consistency and global lower bounds
by: Trillos, Nicolas Garcia, et al.
Published: (2023)
by: Trillos, Nicolas Garcia, et al.
Published: (2023)
Logifold: A Geometrical Foundation of Ensemble Machine Learning
by: Jung, Inkee, et al.
Published: (2024)
by: Jung, Inkee, et al.
Published: (2024)
Riemannian Integrated Gradients: A Geometric View of Explainable AI
by: Costanza, Federico, et al.
Published: (2025)
by: Costanza, Federico, et al.
Published: (2025)
Fiber Bundle Networks: A Geometric Machine Learning Paradigm
by: Liu, Dong
Published: (2025)
by: Liu, Dong
Published: (2025)
Jet Functors and Weil Algebras in Automatic Differentiation: A Geometric Analysis
by: Sangha, Amandip
Published: (2025)
by: Sangha, Amandip
Published: (2025)
TopoGeoScore: A Self-Supervised Source-Only Geometric Framework for OOD Checkpoint Selection
by: Hazratian, Farid, et al.
Published: (2026)
by: Hazratian, Farid, et al.
Published: (2026)
Kernel-Gradient Drifting Models
by: Esteban-Casadevall, Maria, et al.
Published: (2026)
by: Esteban-Casadevall, Maria, et al.
Published: (2026)
Minimising Willmore Energy via Neural Flow
by: Hirst, Edward, et al.
Published: (2026)
by: Hirst, Edward, et al.
Published: (2026)
Interpretable Analytic Calabi-Yau Metrics via Symbolic Distillation
by: Eng, D Yang
Published: (2026)
by: Eng, D Yang
Published: (2026)
Steerable Neural ODEs on Homogeneous Spaces
by: Andersdotter, Emma, et al.
Published: (2026)
by: Andersdotter, Emma, et al.
Published: (2026)
Complex normalizing flows can almost be information Kähler-Ricci flows
by: Gracyk, Andrew
Published: (2026)
by: Gracyk, Andrew
Published: (2026)
Geometric and Spectral Alignment for Deep Neural Network I
by: Liu, Ziran, et al.
Published: (2026)
by: Liu, Ziran, et al.
Published: (2026)
Geometric and Spectral Alignment for Deep Neural Network II
by: Liu, Ziran, et al.
Published: (2026)
by: Liu, Ziran, et al.
Published: (2026)
Barycentric subspace analysis of network-valued data
by: Maignant, Elodie, et al.
Published: (2025)
by: Maignant, Elodie, et al.
Published: (2025)
Learning Beyond Euclid: Curvature-Adaptive Generalization for Neural Networks on Manifolds
by: Sarkar, Krisanu
Published: (2025)
by: Sarkar, Krisanu
Published: (2025)
Hardness of Learning Neural Networks under the Manifold Hypothesis
by: Kiani, Bobak T., et al.
Published: (2024)
by: Kiani, Bobak T., et al.
Published: (2024)
Cartan moving frames and the data manifolds
by: Tron, Eliot, et al.
Published: (2024)
by: Tron, Eliot, et al.
Published: (2024)
Universal Collection of Euclidean Invariants between Pairs of Position-Orientations
by: Bellaard, Gijs, et al.
Published: (2025)
by: Bellaard, Gijs, et al.
Published: (2025)
Roto-Translation Invariant Metrics on Position-Orientation Space
by: Bellaard, Gijs, et al.
Published: (2025)
by: Bellaard, Gijs, et al.
Published: (2025)
Flow Matching on Lie Groups
by: Sherry, Finn M., et al.
Published: (2025)
by: Sherry, Finn M., et al.
Published: (2025)
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
by: Kohli, Dhruv, et al.
Published: (2025)
by: Kohli, Dhruv, et al.
Published: (2025)
Discretized Gradient Flow for Manifold Learning in the Space of Embeddings
by: Gold, Dara, et al.
Published: (2019)
by: Gold, Dara, et al.
Published: (2019)
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds
by: Sun, Xingzhi, et al.
Published: (2024)
by: Sun, Xingzhi, et al.
Published: (2024)
Deep Generative Models: Complexity, Dimensionality, and Approximation
by: Wang, Kevin, et al.
Published: (2025)
by: Wang, Kevin, et al.
Published: (2025)
Distance Measure Based on an Embedding of the Manifold of K-Component Gaussian Mixture Models into the Manifold of Symmetric Positive Definite Matrices
by: Vishwakarma, Amit, et al.
Published: (2025)
by: Vishwakarma, Amit, et al.
Published: (2025)
Persistent de Rham-Hodge Laplacians in Eulerian representation for manifold topological learning
by: Su, Zhe, et al.
Published: (2024)
by: Su, Zhe, et al.
Published: (2024)
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows
by: Diepeveen, Willem, et al.
Published: (2024)
by: Diepeveen, Willem, et al.
Published: (2024)
Universal kernels via harmonic analysis on Riemannian symmetric spaces
by: Steinert, Franziskus, et al.
Published: (2025)
by: Steinert, Franziskus, et al.
Published: (2025)
Revealing Decurve Flows for Generalized Graph Propagation
by: Lin, Chen, et al.
Published: (2024)
by: Lin, Chen, et al.
Published: (2024)
Tangentially Aligned Integrated Gradients for User-Friendly Explanations
by: Simpson, Lachlan, et al.
Published: (2025)
by: Simpson, Lachlan, et al.
Published: (2025)
Thinner Latent Spaces: Detecting Dimension and Imposing Invariance with Conformal Autoencoders
by: Kevrekidis, George A., et al.
Published: (2024)
by: Kevrekidis, George A., et al.
Published: (2024)
Simultaneous Optimization of Geodesics and Fréchet Means
by: Rygaard, Frederik Möbius, et al.
Published: (2025)
by: Rygaard, Frederik Möbius, et al.
Published: (2025)
Staying on the Manifold: Geometry-Aware Noise Injection
by: Jacobsen, Albert Kjøller, et al.
Published: (2025)
by: Jacobsen, Albert Kjøller, et al.
Published: (2025)
Geometric Learning with Positively Decomposable Kernels
by: Da Costa, Nathael, et al.
Published: (2023)
by: Da Costa, Nathael, et al.
Published: (2023)
Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian Geometry
by: Diepeveen, Willem, et al.
Published: (2025)
by: Diepeveen, Willem, et al.
Published: (2025)
Riemannian Variational Flow Matching for Material and Protein Design
by: Zaghen, Olga, et al.
Published: (2025)
by: Zaghen, Olga, et al.
Published: (2025)
Similar Items
-
Continual Learning as a Multiphase Moving-Boundary Problem
by: Khilar, Snigdha Chandan
Published: (2026) -
PFlow-T: A Persistence-Driven Forward Process for Topology-Controlled Generation
by: Khilar, Snigdha Chandan
Published: (2026) -
A singular Riemannian Geometry Approach to Deep Neural Networks III. Piecewise Differentiable Layers and Random Walks on $n$-dimensional Classes
by: Benfenati, Alessandro, et al.
Published: (2024) -
On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization
by: Shumaylov, Zakhar, et al.
Published: (2025) -
Continuum Limits of Ollivier's Ricci Curvature on data clouds: pointwise consistency and global lower bounds
by: Trillos, Nicolas Garcia, et al.
Published: (2023)