The Platform trial In COVID-19 vaccine priming and BOOsting (PICOBOO) booster vaccination substudy protocol by McLeod C, Dymock M, Flanagan KL, Plebanski M, Marshall H, Marsh J, Estcourt MJ, Ramsay J, Wadia U, Williams PCM, Tjiam MC, Blyth C, Subbarao K, Nicholson S, Faust S.N., Thornton RB, Mckenzie A, Snelling T, Richmond P

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Primary user characterization for cognitive radio wireless networks using long short-term memory by Johana Hernández, Danilo López, Nelson Vera

“…The results show that long short-term memory has the capacity needed to improve channel use forecasting significantly more than other methods such as multilayer perceptron neural networks, Bayesian networks, and adaptive neuro-fuzzy inference systems (ANFIS-Grid). …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…A Bayesian Optimization algorithm was employed for the selection of hyperparameters. …”
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SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation by Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro

“…These capabilities make SageNet a powerful tool for accelerating Bayesian inference procedures for extended cosmological models. …”
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A Kalman Framework Based Mobile Node Localization in Rough Environment Using Wireless Sensor Network by Hao Chu, Cheng-dong Wu

“…Then the modified variational Bayesian approximation adaptive Kalman filtering is used to mitigate the NLOS error. …”
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Neural Network-Based Optimization for Bandwidth Enhancement of Millimeter-Wave Franklin Antenna With Proximity-Coupled Feed by Ahmad Firdausi, Eko Setijadi, Gamantyo Hendrantoro, Mudrik Alaydrus

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Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks by Diaoulé Diallo, Jurij Schoenfeld, René Schmieding, Sascha Korf, Martin J. Kühn, Tobias Hecking

“…This paper presents an integrated approach for generating such networks by coupling Bayesian-optimized human mobility models (HuMMs) with a state-of-the-art epidemic simulation framework. …”
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Estimation of Relative Sea Level Change in Locations Without Tide Gauges Using Artificial Neural Networks by Heeryun Kim, Young Il Park, Wansik Ko, Taehyun Yoon, Jeong-Hwan Kim

“…This study aims to develop an artificial neural network-based model for estimating relative sea level changes in coastal regions where tide gauge data are unavailable. …”
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Heterogeneous transfer learning model for improving the classification performance of fNIRS signals in motor imagery among cross-subject stroke patients by Jin Feng, YunDe Li, ZiJun Huang, Yehang Chen, SenLiang Lu, RongLiang Hu, QingHui Hu, YuYao Chen, XiMiao Wang, Yong Fan, Jing He

“…This study proposes a Cross-Subject Heterogeneous Transfer Learning Model (CHTLM) to enhance the generalization of MI-fNIRS signal classification in stroke patients.MethodsCHTLM leverages labeled electroencephalogram (EEG) data from healthy individuals as the source domain. An adaptive feature matching network aligns task-relevant feature maps and convolutional layers between source (EEG) and target (fNIRS) domains. …”
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Research on Application of Big Data in Internet Financial Credit Investigation Based on Improved GA-BP Neural Network by Fei-Peng Wang

“…Then, the Internet financial credit data are preprocessed, the variables suitable for modeling are selected, and the dynamic credit tracking model of BP neural network based on adaptive genetic algorithm is constructed. …”
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A Typical Infrared Background Radiation Prediction Model Based on RF-VMD and Optimized Hybrid Neural Network by Bentian Hao, Weidong Xu, Xin Yang, Feifei Xiao, Hao Li, Wei Huang

“…Based on the superimposed IMFs as inputs, a hybrid deep neural network prediction model is established. The model optimizes the CNN-LSTM network with residual connections and introduces a multi-head self-attention mechanism to enhance spatiotemporal feature extraction of the multidimensional meteorological parameters, focusing on key temporal feature regions. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…Experimental results demonstrate that the proposed model significantly outperforms existing methods such as Grid Search RF, Bayesian Optimized RF, Gradient Boosting, and Deep Neural Networks. …”
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Comparative assessment of standalone and hybrid deep neural networks for modeling daily pan evaporation in a semi-arid environment by Mohammed Achite, Manish Kumar, Nehal Elshaboury, Aman Srivastava, Ahmed Elbeltagi, Ali Salem

“…Conventional deep neural network (DNN) coupled with support vector machine (SVM), Bayesian additive regression trees (BART), random subspace (RSS), M5 pruned, and random forest (RF) were used for developing prediction models using various input variable combinations. …”
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An artificial intelligence approach to palaeogeographic studies: a case study of the Late Ordovician brachiopods of Laurentia by Akbar Sohrabi

“…For training the neural network model, the Bayesian training function (trainbr) was used. …”
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Physics-Informed Neural Networks: A Review of Methodological Evolution, Theoretical Foundations, and Interdisciplinary Frontiers Toward Next-Generation Scientific Computing by Zhiyuan Ren, Shijie Zhou, Dong Liu, Qihe Liu

“…The contributions include threefold: First, identifying the co-evolutionary path of algorithmic architectures from adaptive optimization (neural tangent kernel-guided weighting achieving 230% convergence acceleration in Navier-Stokes solutions) to hybrid numerical-deep learning integration (5× speedup via domain decomposition) and second, constructing bidirectional theory-application mappings where convergence analysis (operator approximation theory) and generalization guarantees (Bayesian-physical hybrid frameworks) directly inform engineering implementations, as validated by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>72</mn><mo>%</mo></mrow></semantics></math></inline-formula> cost reduction compared to FEM in high-dimensional spaces (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.01</mn><mo>,</mo><mi>n</mi><mo>=</mo><mn>15</mn></mrow></semantics></math></inline-formula> benchmarks). …”
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Transmitted drug resistance in the CFAR network of integrated clinical systems cohort: prevalence and effects on pre-therapy CD4 and viral load. by Art F Y Poon, Jeannette L Aldous, W Christopher Mathews, Mari Kitahata, James S Kahn, Michael S Saag, Benigno Rodríguez, Stephen L Boswell, Simon D W Frost, Richard H Haubrich

“…The overall prevalence of TDR was 14.2%. We used a Bayesian network to identify co-transmission of TDR mutations in clusters associated with specific drugs or drug classes. …”
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Diagnostic yield of nine user-friendly bioinformatics tools for predicting Mycobacterium tuberculosis drug resistance: A systematic review and network meta-analysis. by Ya-Li Chen, Yu He, Victor Naestholt Dahl, Kan Yu, Yan-An Zhang, Cui-Ping Guan, Mao-Shui Wang

“…Data were collected and pooled using random-effects meta-analysis and Bayesian network meta-analysis (NMA). Summary receiver operating characteristic curves (SROCs) analysis were performed, and superiority index (SI) and area under the curve (AUC) were calculated. …”
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Deep learning-based image classification for integrating pathology and radiology in AI-assisted medical imaging by Chenming Lu, Jiayin Zhang, Ren Liu

“…These limitations often hinder the deployment of AI systems in real-world clinical settings, where reliability and adaptability are essential. To address these issues, this study introduces a novel framework, the Domain-Informed Adaptive Network (DIANet), combined with an Adaptive Clinical Workflow Integration (ACWI) strategy. …”
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A Novel Deep Learning Architecture for Agriculture Land Cover and Land Use Classification from Remote Sensing Images Based on Network-Level Fusion of Self-Attention Architecture by Hussain Mobarak Albarakati, Muhammad Attique Khan, Ameer Hamza, Faheem Khan, Naoufel Kraiem, Leila Jamel, Latifah Almuqren, Roobaea Alroobaea

“…After that, we trained the model and performed classification using neural network (NN) classifiers. The results obtained from the NN classifiers are insufficient; therefore, we implemented a Bayesian optimization and fine-tuned the hyperparameters of NN. …”
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Comparative effectiveness of different transarterial embolization therapies alone or in combination with local ablative or adjuvant systemic treatments for unresectable hepatocellu... by Konstantinos Katsanos, Panagiotis Kitrou, Stavros Spiliopoulos, Ioannis Maroulis, Theodore Petsas, Dimitris Karnabatidis

“…We conducted a systematic review and network meta-analysis (NMA) of different embolization options for unresectable HCC.…”
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