Results 41 to 50 of about 133,961 (310)

Network meta-analysis: application and practice using R software [PDF]

Epidemiology and Health, 2019
The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software.
Sung Ryul Shim, Seong-Jang Kim, Jonghoo Lee, Gerta Rücker   +3 more
doaj   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data. [PDF]

PLoS ONE, 2017
Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell.
Zahra Narimani, Hamid Beigy, Ashar Ahmad, Ali Masoudi-Nejad, Holger Fröhlich   +4 more
doaj   +1 more source

Hybrid time Bayesian networks

International Journal of Approximate Reasoning, 2015
Capturing heterogeneous dynamic systems in a probabilistic model is a challenging problem. A single time granularity, such as employed by dynamic Bayesian networks, provides insufficient flexibility to capture the dynamics of many real-world processes.
Peter J. F. Lucas, Arjen Hommersom, Arjen Hommersom, Maarten van der Heijden, Manxia Liu   +4 more
openaire   +8 more sources

Algebraic Geometry of Bayesian Networks

Journal of Symbolic Computation, 2003
We study the algebraic varieties defined by the conditional independence statements of Bayesian Networks. A complete algebraic classification is given for Bayesian Networks on at most five random variables. Hidden variables are related to the geometry of higher secant varieties.
Luis David García Puente, Michael Stillman, Bernd Sturmfels   +2 more
openalex   +5 more sources

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

Additive Bayesian Networks

Journal of Open Source Software
The R package abn is a comprehensive tool for Bayesian Network (BN) analysis, a form of probabilistic graphical model. BNs are a type of statistical model that leverages the principles of Bayesian statistics and graph theory to provide a framework for representing complex multivariate data.
Delucchi, Matteo, Liechti, Jonas I, Spinner, Georg R, Furrer, Reinhard   +3 more
openaire   +2 more sources

Gaussian‐Sigmoid Reinforcement Transistors: Resolving Exploration‐Exploitation Trade‐Off Through Gate Voltage‐Controlled Activation Functions

Advanced Functional Materials, EarlyView.
The characteristics of a vertical n–p–i–p heterostructure transistor device, which exhibits a voltage‐tunable transition between Gaussian and sigmoid functions, are investigated. The mixed state of the transfer curve enables the utilization of both exploitation and exploration, improving computational performance in reinforcement learning tasks ...
Jisoo Park, Juhyung Seo, Ryun‐Han Koo, Dinithi Jayasuriya, Nethmi Jayasinghe, Wonjun Shin, Amit R. Trivedi, Hocheon Yoo   +7 more
wiley   +1 more source

Energy financial risk early warning model based on Bayesian network

Energy Reports, 2023
Oil is a global, non-renewable energy source, which plays a pivotal role in the development of the global economy and the strategic reserve system. With the expansion of crude oil futures trading scale, crude oil is no longer a pure energy commodity, but
Lin Wei, Hanyue Yu, Bin Li
doaj  

Antitumoral Efficacy of AuNRs‐Laden ECFCs In Vitro and In Vivo: Decoding the Heat and Rays Combo Treatment in Breast Cancer and Melanoma Cells

Advanced Healthcare Materials, EarlyView.
Endothelial Colony Forming Cells (ECFCs) acted as cellular cyborgs, stealthily transporting gold nanorods (AuNRs) into tumors to enable targeted near‐infrared (NIR) hyperthermia combined with radiotherapy. This approach triggers ferroptosis in melanoma and inhibits autophagy in breast cancer, revealing a tumor‐specific response to nanomaterial‐assisted
Cecilia Anceschi, Francesca Scavone, Paolo Armanetti, Luca Menichetti, Claudia Catarinicchia, Claudia Borri, Fulvio Ratto, Filippo Micheletti, Noemi Formica, Jessica Ruzzolini, Elena Frediani, Anastasia Chillà, Francesca Margheri, Mirko Severi, Rita Traversi, Patrizia Nardini, Daniele Guasti, Mario Del Rosso, Tommaso Del Rosso, Lisa Giovanelli, Cinzia Talamonti, Monica Mangoni, Isacco Desideri, Silvia Burchielli, Fabiola Pajar, Gabriella Fibbi, Anna Laurenzana   +26 more
wiley   +1 more source