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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

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Preprint Aug 2026

Weighted Laplacian Flow: A Deterministic Particle Flow with Exponential Convergence

We introduce weighted Laplacian flow (WLF), a deterministic particle-flow framework for sampling from a target distribution known only up to normalization. The proposed method evolves the logarithmic density ratio through a transport equation and determines the particle velocity from a target-weighted Poisson problem,...

Wei-Ye Gan, Tang-Jun Wang, Zuo-Qiang Shi · 0 citations
Preprint Aug 2026

Diffusion Quasi-Monte Carlo

This work constructs a cube-to-target map by composing a Gaussian base transformation (the component-wise inverse Gaussian CDF) with an Euler-discretized probability flow ODE, and establishes conditions for diffusion probability-flow transport under mild bounded-derivative assumptions on the learned vector field.

Jian-Long Chen, Yi-Feng Yu · 0 citations
Preprint Aug 2026

Ordered Diffusion Kernels

We introduce Ordered Diffusion Kernels (ODKs), a novel class of local kernels that can approximate the infinitesimal generator of an arbitrary It\^o Stochastic Differential Equation (SDE). ODKs are designed to be applied to data sampled from dynamical systems where little dynamical information is available a priori. Th...

Jack H. Soulsby, A. C. S. Jørgensen, Atiyo Ghosh et al. · 0 citations
Preprint Aug 2026

Convergence of time-discrete finite particle consensus based optimization in Hilbert spaces

This analysis provides convergence guarantees directly for the computable particle system, complementing recent continuous-time and mean-field results in infinite dimensions and establishing quantitative pairwise contraction, exponential decay of the expected swarm variance, and almost-sure convergence of all particles...

Michael Herty, Hui Huang, Hicham Kouhkouh · 0 citations
#diffusion models Open access Sep 2026

Mean-field path-integral diffusion from samples to interacting agents

Moving probability distributions in the context of stochastic processes efficiently is central to modern generative modeling, uncertainty quantification, and control of large engineered systems. Most current methods generate temporal trajectories independently, leaving open whether the trajectories can cooperate throug...

M. Chertkov · 0 citations
Preprint Oct 2026

Deterministic and stochastic particle methods for the Fokker-Planck equation in S--formulation with application to point set registration

We present two particle methods for point set registration in bounded domains based on the Fokker-Planck equation. The first method relies on a moving least squares discretization of the S--formulation, in which moving grid points (particles) are advected by the drift with the target distribution, diffusion is resolved...

Klaas Willems, A. Iollo, G. Russo et al. · 0 citations

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