Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Using DREAM4’s Gene Net Weaver and Sachs protein signaling data, we assess the effectiveness of different strategies in improving network learning. Conclusion Existing Bayesian experiment design strategies often overlook the Essential Graph structure, making inference more challenging due to the large number of possible graphs. …”
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Splinting in horizontal root fractures: A Bayesian network meta-analysis. by Tatiana Carvalho Kowaltschuk, Flávio Magno Gonçalves, Bianca Marques de Mattos de Araujo, Natália Teixeira da Silva Cruz, Angela Graciela Deliga Schroder, Bruna Belz Antoniazzi, Everdan Carneiro, Marisa Nogueira Alencar, Ulisses Xavier da Silva-Neto, Odilon Guariza-Filho, Cristiano Miranda de Araujo, Vânia Portela Ditzel Westphalen

“…The risk of bias in the included studies was assessed using the Joanna Briggs Institute Critical Appraisal tools. A Bayesian network meta-analysis was conducted.<h4>Results</h4>A total of 3,174 references were retrieved, of which six studies met the inclusion criteria. …”
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Quantifying Uncertainty in Projections of Desertification in Central Asia Using Bayesian Networks by Jinping Liu, Yanqun Ren, Panxing He, Jianhua Xiao

“…These results highlight the utility of Bayesian networks as an effective tool for desertification assessment and scenario analysis, underscoring the urgency of targeted land management and proactive climate adaptation. …”
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Bayesian network modeling of flood cascade and climate risks in the Pearl River Delta by Wen Zhang, Jianglong Cui, Weike Yao, Mariavittoria Guida, Frederick Kwame Yeboah, Xuanru Zhou, Yafei Li, Lixiao Zhang, Gengyuan Liu

“…This study develops a Bayesian network model to assess flood control infrastructure vulnerability (including flood susceptibility and critical failure nodes) and cascading failures in the Pearl River Delta (PRD) under future climatic scenarios. …”
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Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

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Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach by João Miguel Alves, Daniel Matos, Tiago Martins, Diogo Cavaco, Pedro Carmo, Pedro Galvão, Francisco Moscoso Costa, Francisco Morgado, António Miguel Ferreira, Pedro Freitas, Cláudia Camila Dias, Pedro Pereira Rodrigues, Pedro Adragão

“…ObjectiveThis study aims to investigate the effectiveness of Bayesian networks as a predictive tool for AF relapse following a percutaneous pulmonary vein isolation (PVI) procedure. …”
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The Using Bayesian Networks and Fuzzy Logic to Predict Warehouse Planning Disruption Risks by Kerouich Abdelilah, Azmani Abdellah, Azmani Monir

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Robust Bayesian analysis of animal networks subject to biases in sampling intensity and censoring by Sebastian Sosa, Mary B. McElreath, Daniel Redhead, Cody T. Ross

“…Here, we address the issue by developing a Bayesian model, which not only estimates network structure but also explicitly accounts for sampling and censoring biases. …”
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Adaptive DecayRank: Real-Time Anomaly Detection in Dynamic Graphs with Bayesian PageRank Updates by Ocheme Anthony Ekle, William Eberle, Jared Christopher

“…Our method extends the dynamic PageRank algorithm by incorporating an adaptive Bayesian updating mechanism, allowing nodes to dynamically adjust their decay factors based on observed graph changes. …”
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An AI-Based Decision Support System Utilizing Bayesian Networks for Judicial Decision-Making by Zlatan Morić, Vedran Dakić, Siniša Urošev

“…This study investigates the application of Bayesian networks in structuring legal evidence within an AI-based decision support system. …”
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SBCS-Net: Sparse Bayesian and Deep Learning Framework for Compressed Sensing in Sensor Networks by Xianwei Gao, Xiang Yao, Bi Chen, Honghao Zhang

“…This framework innovatively expands the iterative process of sparse Bayesian compressed sensing using convolutional neural networks and Transformer. …”
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Compressed CNN Plant Leaf Ｒecognition Model Fused with Bayesian by YAN Ming, ZHU Liang-kuan, JING Wei-peng

“…Aiming at the problem that there are many parameters in the process of plant leaf recognition and it is easy to produce over-fitting，in order to reduce the cost of storage and calculation，this paper proposes a plant leaf recognition convolutional neural network model based on Bayesian fusion. Firstly，the recursive Bayesian algorithm is used for network pruning to adaptively remove network redundancy. …”
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Uncertainty-Aware Earthquake Forecasting Using a Bayesian Neural Network with Elastic Weight Consolidation by Changchun Liu, Yuting Li, Huijuan Gao, Lin Feng, Xinqian Wu

“…To address these challenges, we propose a Bayesian neural network (BNN) framework based on Stein variational gradient descent (SVGD). …”
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Enhanced Network Traffic Classification Using Bayesian-Optimized Logistic Regression and Random Forest Algorithm by Manisankar Sannigrahi, R. Thandeeswaran

“…Compared to other machine learning algorithms, the proposed models demonstrate superior performance in balancing accuracy, computational efficiency, and detection speed, making them ideal for real-time network security applications. This approach’s flexibility to adapt to various network conditions and datasets ensures consistent optimal performance as traffic patterns change.…”
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A template Bayesian network for combining forensic evidence on an item with an uncertain relation to the disputed activities by M. Vink, J.A. de Koeijer, M.J. Sjerps

“…This study presents a template Bayesian network (BN) for the evaluation of transfer evidence given activity level propositions considering a dispute about the relation of an item to one or more activities. …”
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Accident Diagnosis and Evaluation System in Parking Lots Using Multisource Data Based on Bayesian Networks by Yijing Zhang, Zhan Zhang, Zhenyu Wang, Tongtong Lyu, Xianing Wang, Linjun Lu

“…The mutual information method is used to screen the possible influencing factors before modeling to reduce the subjectivity of Bayesian networks. Studying the cause and effect analysis of accidents provides diagnosis and prediction for property damage and event causes. …”
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Scalable variational learning for noisy-OR Bayesian networks with normalizing flows for complex cascading disaster systems by Xuechun Li, Susu Xu

“…We present online-DisasterVINF, a framework addressing both challenges through Noisy-OR Bayesian networks and normalizing flows. This approach models how multiple hazards independently contribute to observed impacts while providing a more expressive alternative to log-linear relationships. …”
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A network intrusion detection method based on contrastive learning and Bayesian Gaussian Mixture Model by Liyou Liu, Ming Xu

“…Abstract Network Intrusion Detection Systems (NIDS) are essential for safeguarding networks against malicious activities. …”
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Flood risk assessment for road infrastructures using Bayesian networks: case study of Santarem - Portugal by Erica Arango, Monica Santamaria, Maria Nogal, Hélder S. Sousa, José C. Matos

“…To this end, a Flood Risk Factor (FRF) is computed as a function of hazard, vulnerability, and infrastructure importance factors. A Bayesian Network (BN) is constructed for considering the interdependencies among the selected input factors, as well as accounting for the uncertainties involved in the modelling process. …”
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Bayesian curriculum generation in sparse reward reinforcement learning environments by Onur Akgün, N. Kemal Üre

“…Diverging from traditional methodologies, this algorithm utilizes Bayesian networks to dynamically create tasks by altering problem parameters, thereby impacting task difficulty. …”
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