diffusion models

UED Reconstruction Programme — Paper 2: Ripple Dynamics in SVE

Paper 2 develops the first non-classical dynamical layer of the UED Reconstruction Programme: a minimal local-coupling description of ripple dynamics in Structured Vacuum Energy (SVE). Rather than assuming a mechanical wave, electromagnetic field, particle stream, or moving medium, the reconstruction introduces two ope...

A Simple Clinical–MRI Model Combining Tumor Mobility and ADC for Preoperative Prediction of Malignancy in Parotid Gland Tumors

Artificial Intelligence, Machine Learning, and Deep Learning Concepts, Methods, and Real-World Impact

This chapter presents an accessible yet technically grounded overview of the relationship among AI, ML, and DL, tracing their historical development from early symbolic reasoning and theoretical foundations to modern neural networks and transformer-based systems.

Generative AI as a Third Agent: Rethinking Academic Work and Principal-Agent Dynamics in Higher Education

The rapid diffusion of generative AI in higher education is transforming academic work in ways that extend beyond technical efficiency or pedagogical innovation, reaching the foundations of institutional authority, human agency, and educational purpose. This paper develops a nested principal–agent model in which genera...

Generative diffusion models for spatiotemporal influenza forecasting

Forecasting infectious disease incidence can provide important information to guide public health planning, yet it is difficult because epidemic dynamics are complex. Current mechanistic and statistical approaches often struggle to capture multimodal uncertainty or emergent trends. Influpaint adapts denoising diffusion...

Exploring the Potential of Diffusion Large Language Models in Code Generation

This study presents the first empirical study of diffusion LLMs for code generation and explores factors impacting the effectiveness and efficiency of diffusion LLMs, and provides practical guidance.

mmDif-DRL:Diffusion-Deep Reinforcement Learning for Collaborative mmWave Positioning

In emergency rescue scenarios, such as fires where smoke and dust reduce visibility, millimeter-wave (mmWave) radar offers advantages over vision-based localization due to its penetration capability and adaptability to harsh environments. Nevertheless, signal sparsity, multipath interference, and the high cost of data...

From Automated Coding to Qualitative Intelligence: A Human-Governed AI Model for Interpretive Research

The model is based on the principles of interpretivist epistemology, construct-validity theory, and human-in-the-loop (HITL) AI principles and redefines AI as an enhancement tool and not an autonomous interpreter, which sets a conceptual background to future empirical verification of AI systems run by humans.

Explainable Artificial Intelligence in Mental Health Assessment: A Systematic Review of Interpretability, Psychometric Reporting and Clinical Utility

The model is based on the principles of interpretivist epistemology, construct-validity theory, and human-in-the-loop (HITL) AI principles and redefines AI as an enhancement tool and not an autonomous interpreter, which sets a conceptual background to future empirical verification of AI systems run by humans.

A novel channel-encoder latent diffusion models for in vivo human brain spectral reconstruction

Dual pore network modeling of coupled gas transport and electrochemical reactions in the cathode catalyst layer considering oxygen diffusion barriers at void–ionomer connections

Robust and Fast Binary Fringe Projection Profilometry With Error Diffusion Model

For scientific and industrial applications requiring high-accuracy and high-speed 3D shape measurement, in this Letter we propose a robust and fast binary fringe projection profilometry (BFPP) method that transcends the traditional paradigm of binary defocusing. First, a perturbed error diffusion algorithm is employed...