Results 191 to 200 of about 523,565 (314)

A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders [PDF]

Christophe Gonzales, Abdollah Valizadeh
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

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

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

Learning Bayesian Networks with the bnlearn Python Package.

Taskesen, Erdogan
openalex   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

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, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Comparison of multiple doses of corticosteroids in Kawasaki disease: a Bayesian network analysis. [PDF]

Front Pharmacol
Li X, Tang X, Yang D, Hou M, Xu Q, Tang Y, Wang B, Huang H, Chen Y, Liu Z, Qian G, Lv H.   +11 more
europepmc   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Endovascular treatment for basilar artery occlusion: A Bayesian network meta-analysis comparing time-to-treatment windows and medical management. [PDF]

Neuroradiol J
Carretta LTA, Gonçalves OR, Falcão L, de Bastos Maximiano ML, Mitre LP, Arend RB, Fernandes JVA, Teixeira PR, Di Cosmo L, Morais TC, Barbosa LA, Günkan A.   +11 more
europepmc   +1 more source

SuperResNET: Model‐Free Single‐Molecule Network Analysis Software Achieves Molecular Resolution of Nup96

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li, Ismail M. Khater, Christian Hallgrimson, Ben Cardoen, Timothy H. Wong, Ghassan Hamarneh, Ivan R. Nabi   +6 more
wiley   +1 more source

Factors influencing late HIV presentation in China: results from logistic regression and Bayesian network analyses. [PDF]

BMC Infect Dis
Zhao HH, Luo DH, Fei LP, Wang S, Chen FF, Qin QQ, Cai C, Jin YC, Xu J, Tang HL, Lyu F.   +10 more
europepmc   +1 more source