Advanced Intelligent Discovery, EarlyView.CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
Replica exchange enhanced adaptively weighted stochastic gradient Langevin dynamics for Bayesian sampling and optimization. [PDF]
Sci RepWu Z, Gong W, Yu Z, Zhu L, Yang L.
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Incorporating spatial diffusion into models of bursty stochastic transcription. [PDF]
J R Soc InterfaceMiles CE.
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
A Neoteric Three-Dimensional Geometry-Based Stochastic Model for Massive MIMO Fading Channels in Subway Tunnels [PDF]
, 2019 Yukang Jiang +3 more
openalex +1 more source
Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
Advanced Intelligent Systems, EarlyView.This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen +4 more
wiley +1 more source
Comparative analysis of convolutional neural networks and vision transformers in identifying benign and malignant breast lesions. [PDF]
Medicine (Baltimore)Wang L, Fang S, Chen X, Pan C, Meng M.
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
Neurons exploit stochastic growth to rapidly and economically build dense dendritic arbors. [PDF]
Nat CommunOuyang X +6 more
europepmc +1 more source