diffusion models

A comprehensive mathematical model for cancer metastasis induction: Qualitative analysis and numerical experiments

Tumors pose a significant threat to human health, and traditional treatment methods have limitations in controlling their growth and spread. This article utilizes combined mathematical and physical models to investigate tumor diffusion and development laws, particularly focusing on the microenvironment induction stage...

A bio-inspired model for cluster optimization in software-defined networks

Effect of Breaking Speed on Plasma Distribution Characteristics During the Arc Extinction Process

Abstract During the tripping of a direct current (DC) vacuum circuit breaker, a plasma arc is generated between the contacts.Different tripping speeds alter the plasma diffusion space between the contacts, affecting the plasma ' s longitudinal and axial diffusion rates. Under identical commutation gap conditions, tripp...

cf-uncertainty: epistemic and aleatoric uncertainty in learned car-following

Nine strengthening items after the extension of v1.4.0, their code, configurations, analysis tables and the compact tables c25-c31 of the extended manuscript. Plan and reading rules: extension/docs/PLAN.md, section S. Code. The model-spec key sampler of an E3 variant (DiffusionCF.configure_sampler: re-planning interval...

Privacy-Preserving Diffusion Against Identity Inference Attack via Semantic Destruction Recovery and Segmentation

Facial image generation or generative editing using diffusion models presents risks of identity leakage, potentially enabling unauthorized re-identification in forensic and content moderation applications. Diffusion editing is vulnerable to privacy-preserving facial identity obfuscation through diffusion-based semantic...

$S^{7}$: Statistics and Stochastics for Sheaves, Shapes, Stratified and Sub-Riemannian Structures

The mathematical description of shapes as elements of non-linear geometric spaces has been central to the field of geometric statistics and has spawned a variety of new links to other fields of mathematics: Geometric data requires models for stochastic processes in geometric spaces, for example, for data in structural...

Application of Bayesian-Derived Gene Interaction Network and Subnetwork for Classification of Idiopathic Parkinson Disease with Biomarkers

Given the expenses associated with Parkinson Disease (PD), it is imperative to develop a method for accurate diagnosis before emergence of motor symptoms. While there are tests that can measure early onset of PD, these tests still rely on subjective input from patients and can thus be biased. Factors influencing their...

Study of Drift-hopping Mechanism for Diffusion in Silicate Glasses using Molecular Dynamics Simulation

Evaluating ensemble ranking fusion for multi-source localization in propagation graphs

Source identification in propagation graphs is an inverse problem that aims to recover the initial infected or activated nodes from an observed propagation snapshot. This paper studies a static, structure-driven setting in which temporal traces, observer timestamps, and large labeled diffusion histories are unavailable...

Knowledge Transfer in MNEs

This chapter conceptualizes the MNE as a knowledge-based and institutionally embedded organization. Moving beyond traditional asset-exploitation views, it examines how competitive advantage depends on the generation, transfer, and recombination of knowledge across borders. The chapter introduces the knowledge-based vie...

Durability of coastal RC envelopes in salt-spray environments: A study through integrated normalized phase-field and dynamic THMC modeling

The long-term performance of building envelopes in coastal regions is severely challenged by salt spray, humidity, and wind-driven rain, which accelerate chloride ingress, steel corrosion, and cracking in reinforced concrete (RC) structures. To accurately capture the coupled degradation processes, this study develops a...

ReCo-Diff: residual-conditioned deterministic sampling for cold diffusion in sparse-view CT

Abstract Objective. Sparse-view computed tomography (CT) reduces radiation dose and acquisition time but introduces structured streak artifacts that make reconstruction severely ill-posed. Cold-diffusion approaches can model such deterministic degradation processes, but existing sampling strategies may rely on scalar s...