惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

IT之家
IT之家
T
Tailwind CSS Blog
V
V2EX
阮一峰的网络日志
阮一峰的网络日志
H
Help Net Security
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
腾讯CDC
GbyAI
GbyAI
酷 壳 – CoolShell
酷 壳 – CoolShell
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Last Week in AI
Last Week in AI
A
About on SuperTechFans
L
LangChain Blog
Engineering at Meta
Engineering at Meta
F
Fortinet All Blogs
G
Google Developers Blog
The Cloudflare Blog
云风的 BLOG
云风的 BLOG
D
Docker
博客园 - 聂微东
博客园 - 司徒正美
Recent Announcements
Recent Announcements
MyScale Blog
MyScale Blog
U
Unit 42

math updates on arXiv.org

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization Non-normal spectral signatures of instability in neural network training dynamics Optimization of randomized neural networks for transfer operator approximation Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Training-Free Looped Transformers Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Asymmetric Scaling Laws from Sparse Features Is Dimensionality a Barrier for Retrieval Models? RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs Commutator-Induced Uncertainty in VAEs Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating Instance-Optimal Estimation with Multiple LLM Judges on a Budget Entropy Equivalence Testing Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation Any-Dimensional Invariant Universality Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Anytime Training with Schedule-Free Spectral Optimization Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology The General Theory of Localization Methods Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Proximal basin hopping: global optimization with guarantees
Isoparametric functions on Finsler space forms
[Submitted on 15 Dec 2022 (v1), last revised 25 Jun 2026 (this v · 2026-06-26 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:In this paper, we prove that transnormal functions are isoparametric functions on Finsler space forms $(N(c),F)$ under certain conditions, which generalize Theorem B given by Q. M. Wang in Riemannian case. On forward Finsler space forms $(\overrightarrow{N}(c),F)$, we discuss the relationship between umbilic hypersurfaces and isoparametric hypersurfaces, and construct global and local isoparametric functions using the distance function.

Submission history

From: Yali Chen [view email]
[v1] Thu, 15 Dec 2022 05:57:31 UTC (12 KB)
[v2] Thu, 14 Mar 2024 04:02:08 UTC (12 KB)
[v3] Tue, 26 Aug 2025 14:02:11 UTC (12 KB)
[v4] Thu, 25 Jun 2026 14:38:40 UTC (13 KB)