Results 171 to 180 of about 113,736 (262)
Integrating artificial neural network-cellular automata and bayesian weight of evidence for spatiotemporal analysis of urban change in Brisbane City [PDF]
Muhamad Iqbal Januadi Putra +1 more
openalex +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Leveraging Deep Learning, Grid Search, and Bayesian Networks to Predict Distant Recurrence of Breast Cancer. [PDF]
Cancers (Basel)Jiang X, Zhou Y, Wells A, Brufsky A.
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Forecasting Subjective Cognitive Decline: AI Approach Using Dynamic Bayesian Networks. [PDF]
J Med Internet ResEtholén A +7 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley +1 more source
Assessing Credibility in Bayesian Networks Structure Learning. [PDF]
Entropy (Basel)Barth V, Serrão F, Maciel C.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Natural Gas Purification Plants Based on Interpretive Structural Models and Bayesian Networks. [PDF]
ACS OmegaGong J +5 more
europepmc +1 more source