Results 101 to 110 of about 85,238 (262)

Incremental Compilation of Bayesian networks

CoRR, 2003
Most methods of exact probability propagation in Bayesian networks do not carry out the inference directly over the network, but over a secondary structure known as a junction tree or a join tree (JT). The process of obtaining a JT is usually termed {sl compilation}. As compilation is usually viewed as a whole process; each time the network is modified,
Flores, Julia, Gámez, José A., Olesen, Kristian Grønborg   +2 more
openaire   +4 more sources

Consensus Formation and Change are Enhanced by Neutrality

Advanced Science, EarlyView.
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag, Janina A. Hoffmann, Tim Rogers, Christian A. Yates   +3 more
wiley   +1 more source

Diagnostic Bayesian networks

Comput. Artif. Intell., 1997
Summary: The paper presents a causal-probabilistic approach to the technical diagnosis in which the solution of the technical diagnostic problem is considered as a probabilistic inference on a special kind of Bayesian networks called diagnostic Bayesian networks.
openaire   +3 more sources

Empirical evaluation of scoring functions for Bayesian network model selection

BMC Bioinformatics, 2012
In this work, we empirically evaluate the capability of various scoring functions of Bayesian networks for recovering true underlying structures. Similar investigations have been carried out before, but they typically relied on approximate learning ...
Liu Zhifa, Malone Brandon, Yuan Changhe
doaj   +1 more source

Single‐Cell Dissection of Therapy‐Induced Remodeling Uncovers a Fibroblast‐Driven Immunosuppressive Niche and Targetable Vulnerabilities in Lethal Prostate Cancer

Advanced Science, EarlyView.
Single‐cell longitudinal profiling reveals that androgen‐deprivation therapy induces a DPT+ fibroblast‐complement axis that suppresses macrophage inflammation and drives CD8+ T cell exhaustion in prostate cancer. Concurrently, resistant epithelial subpopulations persist and engage TSPAN1‐ and NRXN1‐mediated programs promoting CRPC and neuroendocrine ...
Yang Chen, Dandan Dong, Jinling Liao, Naikai Liao, Mengqi Liu, Qin Zhang, Siting Chen, Qi Liu, Ying Lu, Tianyu Li, Chunlin Zou, Qiong Song, Qiuyan Wang, Jian Liang, Qiji Xie, Chengyang Li, Mengyun Wang, Jiwen Cheng, Zengnan Mo, Gong‐Hong Wei   +19 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Inference in Bayesian Networks.

AI Mag., 1999
A Bayesian network is a compact, expressive representation of uncertain relationships among parameters in a domain. In this article, I introduce basic methods for computing with Bayesian networks, starting with the simple idea of summing the probabilities of events of interest. The article introduces major current methods for exact computation, briefly
openaire   +2 more sources

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source