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

V
Visual Studio Blog
博客园 - 司徒正美
Hugging Face - Blog
Hugging Face - Blog
博客园 - 叶小钗
The Cloudflare Blog
D
DataBreaches.Net
J
Java Code Geeks
G
Google Developers Blog
L
LangChain Blog
N
Netflix TechBlog - Medium
Stack Overflow Blog
Stack Overflow Blog
月光博客
月光博客
酷 壳 – CoolShell
酷 壳 – CoolShell
WordPress大学
WordPress大学
小众软件
小众软件
量子位
Apple Machine Learning Research
Apple Machine Learning Research
P
Proofpoint News Feed
博客园_首页
罗磊的独立博客
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
B
Blog
腾讯CDC

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
Time-changed multiparameter Poisson processes and marting...
[Submitted on 16 Jan 2025 (v1), last revised 21 Aug 2026 (this v · 2025-01-16 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:We consider a multiparameter extension of the homogeneous Poisson counting process, namely, the multiparameter Poisson process (MPP). We derive its various distributional properties. Also, we consider an integral of the MPP and analyze its asymptotic distribution. Thereafter, we investigate three time-changed variants of the MPP, where the time-changing components are multivariate subordinator and inverse subordinators with both dependent and independent marginals. Later, we obtain some properties of the multiparameter martingales, which are then used to derive multiparameter martingale characterizations for the MPP and one of its time-changed variants.

Submission history

From: Pradeep Vishwakarma [view email]
[v1] Thu, 16 Jan 2025 13:50:46 UTC (26 KB)
[v2] Fri, 21 Aug 2026 17:33:25 UTC (23 KB)