Cover Image

Learning with Confidence

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Richardson, Oliver Ethan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Differential Geometry
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tensor Gauge Flow Models
by: Strunk, Alexander, et al.
Published: (2025)

Gauge Flow Models
by: Strunk, Alexander, et al.
Published: (2025)

Higher Gauge Flow Models
by: Strunk, Alexander, et al.
Published: (2025)

Carré du champ flow matching: better quality-generalisation tradeoff in generative models
by: Bamberger, Jacob, et al.
Published: (2025)

The Geometric Wall: Manifold Structure Predicts Layerwise Sparse Autoencoder Scaling Laws
by: Zaher, Eslam, et al.
Published: (2026)

Disentanglement Learning via Topology
by: Balabin, Nikita, et al.
Published: (2023)

Pullback Flow Matching on Data Manifolds
by: de Kruiff, Friso, et al.
Published: (2024)

Space filling positionality and the Spiroformer
by: Maurin, M., et al.
Published: (2025)

Variational Geometry-aware Neural Network based Method for Solving High-dimensional Diffeomorphic Mapping Problems
by: Li, Zhiwen, et al.
Published: (2025)

Radial Compensation: Fixing Radius Distortion in Chart-Based Generative Models on Riemannian Manifolds
by: Papamichalis, Marios, et al.
Published: (2025)

Sum-of-Squares Programming for Ma-Trudinger-Wang Regularity of Optimal Transport Maps
by: Shivakumar, Sachin, et al.
Published: (2024)

Geometry-aware similarity metrics for neural representations on Riemannian and statistical manifolds
by: Cayco-Gajic, N Alex, et al.
Published: (2026)

Surrogate-Based Differentiable Pipeline for Shape Optimization
by: Rehmann, Andrin, et al.
Published: (2025)

RETR: Multi-View Radar Detection Transformer for Indoor Perception
by: Yataka, Ryoma, et al.
Published: (2024)

Exploring the Stratified Space Structure of an RL Game with the Volume Growth Transform
by: Curry, Justin, et al.
Published: (2025)

Deep Learning as Ricci Flow
by: Baptista, Anthony, et al.
Published: (2024)

Geometric Learning with Positively Decomposable Kernels
by: Da Costa, Nathael, et al.
Published: (2023)

Hardness of Learning Neural Networks under the Manifold Hypothesis
by: Kiani, Bobak T., et al.
Published: (2024)

Discretized Gradient Flow for Manifold Learning in the Space of Embeddings
by: Gold, Dara, et al.
Published: (2019)

Logifold: A Geometrical Foundation of Ensemble Machine Learning
by: Jung, Inkee, et al.
Published: (2024)

Fiber Bundle Networks: A Geometric Machine Learning Paradigm
by: Liu, Dong
Published: (2025)

Learning Beyond Euclid: Curvature-Adaptive Generalization for Neural Networks on Manifolds
by: Sarkar, Krisanu
Published: (2025)

Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian Geometry
by: Diepeveen, Willem, et al.
Published: (2025)

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds
by: Sun, Xingzhi, et al.
Published: (2024)

A mathematical framework of intelligence and consciousness based on Riemannian Geometry
by: Lu, Meng
Published: (2024)

Aligning the Unseen in Attributed Graphs: Interplay between Graph Geometry and Node Attributes Manifold
by: Labarthe, Aldric, et al.
Published: (2026)

Jet Functors and Weil Algebras in Automatic Differentiation: A Geometric Analysis
by: Sangha, Amandip
Published: (2025)

Barycentric subspace analysis of network-valued data
by: Maignant, Elodie, et al.
Published: (2025)

Universal Collection of Euclidean Invariants between Pairs of Position-Orientations
by: Bellaard, Gijs, et al.
Published: (2025)

Roto-Translation Invariant Metrics on Position-Orientation Space
by: Bellaard, Gijs, et al.
Published: (2025)

Flow Matching on Lie Groups
by: Sherry, Finn M., et al.
Published: (2025)

Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
by: Kohli, Dhruv, et al.
Published: (2025)

Deep Generative Models: Complexity, Dimensionality, and Approximation
by: Wang, Kevin, et al.
Published: (2025)

Riemannian Integrated Gradients: A Geometric View of Explainable AI
by: Costanza, Federico, 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)

Universal kernels via harmonic analysis on Riemannian symmetric spaces
by: Steinert, Franziskus, et al.
Published: (2025)

Tangentially Aligned Integrated Gradients for User-Friendly Explanations
by: Simpson, Lachlan, et al.
Published: (2025)

Simultaneous Optimization of Geodesics and Fréchet Means
by: Rygaard, Frederik Möbius, et al.
Published: (2025)

Staying on the Manifold: Geometry-Aware Noise Injection
by: Jacobsen, Albert Kjøller, et al.
Published: (2025)

Riemannian Variational Flow Matching for Material and Protein Design
by: Zaghen, Olga, et al.
Published: (2025)