Results 141 to 150 of about 96,366 (253)

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Identifying the factors governing internal state switches during nonstationary sensory decision-making. [PDF]

Nat Commun
Mohammadi Z, Ashwood ZC, International Brain Laboratory, Pillow JW.   +3 more
europepmc   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Pulse waveform analysis in Zambian adults living with HIV on antiretroviral therapy: A cross-sectional study of vascular dysfunction. [PDF]

Physiol Rep
Chikopela T, Kaluba L, Mwaanga S, Goma FM.   +3 more
europepmc   +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

Lipid Profile Alterations Across Coronary Heart Disease, Metabolic Syndrome, and Nephrotic Syndrome. [PDF]

J Clin Lab Anal
Tan S, Qu T, Ai J, Fu Y.
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, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Ventilation heterogeneity across A-B-E phenotypes in COPD: insights from spirometry and electrical impedance tomography. [PDF]

Front Med (Lausanne)
Zhang J, Liu T, Chang Z, Dai M, Song L, Yang L, Ti X, Qu S, Zhao Z.   +8 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Markov switching zero-inflated space-time multinomial models for comparing multiple infectious diseases. [PDF]

Biostatistics
Douwes-Schultz D, Schmidt AM, Freitas LP, Carvalho MS.   +3 more
europepmc   +1 more source