Machine learning with knowledge constraints for design optimization of microring resonators as a quantum light source by Parisa Sadeghli Dizaji, Hamidreza Habibiyan

“…Our results demonstrate that by adaptively finding the coupling coefficient through BO, the model has identified optimal points in the over-coupled regions with superior performance. …”
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Time Series Modelling of the Caspian Kutum (Rutilus frisii) Catch Using SARIMA Model by Fateh Moezzi, Hadi Poorbagher, Soheil Eagderi, Jahangir Feghhi

“…However, spatial classification of fishing points resulted in more detailed models andhigher recognition potential of them. …”
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Parameter uncertainty quantification using surrogate models applied to a spatial model of yeast mating polarization. by Marissa Renardy, Tau-Mu Yi, Dongbin Xiu, Ching-Shan Chou

“…The surrogate models also allow rapid Bayesian inference of the parameters via Markov chain Monte Carlo (MCMC) by eliminating model simulations at each step. …”
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Nonlinear Autoregressive Model for Stability and Prediction by Salim M. Ahmad, Anas S. Youns, Manal S. Hamdi

“…The approximation method helped identify the singular point, its stability conditions, and the limit cycle of the proposed model. …”
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Modelling the future of cleaner energy: Explainable artificial intelligence model for green hydrogen production rate estimation by Okorie Ekwe Agwu, Saad Alatefi, Ahmad Alkouh

“…This study addresses this deficiency by developing an accurate and explainable hydrogen yield rate model using Bayesian regularized neural network. …”
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An Evaluation of the Sensitivity of a Source Term Estimation Methodology of Sensor Configuration in an Urban-like Environment by Panagiotis Gkirmpas, Fotios Barmpas, George Tsegas, George Efthimiou, Paul Tremper, Till Riedel, Christos Vlachokostas, Nicolas Moussiopoulos

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Integrated Correction of Nonlinear Dynamic Drift in Terrestrial Mobile Gravity Surveys: A Comparative Study Based on the Northeastern China Gravity Monitoring Network by Zhaohui Chen, Jinzhao Liu

“…The innovative hybrid scheme combines local drift preprocessing (initial-point modeling, line fitting, variance-sum optimization) with global adjustment optimization, achieving the significant suppression of nonlinear drift errors. …”
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Genomic prediction and genetic parameter estimation for unsaturated and saturated fatty acids in Canadian dairy cattle by S. O. Peters, K. Kizilkaya, E. M. Ibeagha-Awemu, X. Zhao

“…Abstract The current study aimed to obtain the estimates of heritabilities and genetic correlations and the prediction abilities and accuracy of Bayesian GBLUP and Bayesian alphabet (BayesA, BayesB, BayesC) models for total and individual monounsaturated, polyunsaturated and saturated fatty acids from Canadian Holstein cows by using genome-wide SNP markers from genotyping-by-sequencing method. …”
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Cancer phylogenetic tree inference at scale from 1000s of single cell genomes by Salehi, Sohrab, Dorri, Fatemeh, Chern, Kevin, Kabeer, Farhia, Rusk, Nicole, Funnell, Tyler, Williams, Marc J., Lai, Daniel, Andronescu, Mirela, Campbell, Kieran R., McPherson, Andrew, Aparicio, Samuel, Roth, Andrew, Shah, Sohrab P., Bouchard-Côté, Alexandre

“…We constructed a phylogenetic model and associated Bayesian inference procedure, sitka, specifically for scWGS data. …”
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Socio‐demographic and geographic disparities in HIV prevalence, HIV testing and treatment coverage: An analysis of 108 national household surveys in 33 African countries by Adrien Allorant, Salome Kuchukhidze, James Stannah, Yiqing Xia, Sanele S. Masuku, Gatien K. Ekanmian, Jeffrey W. Imai‐Eaton, Mathieu Maheu‐Giroux

“…Methods We analysed 108 geo‐referenced population‐based surveys conducted over 2000–2023 across 33 African countries, involving 2.3 million respondents. Multilevel Bayesian logistic regression models assessed associations between HIV outcomes (HIV prevalence, recent HIV testing and ART coverage) and socio‐demographic characteristics (age, education, place of residence, relative wealth), geographic location (country, district) and time trends. …”
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Exploiting full-duplex opportunities in WLANs via a reinforcement learning-based medium access control protocol by Song Liu, Peng Wei

“…Besides, an analytical model is developed to characterize the performance of RLFD. …”
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Stress-Strength Reliability of Two-Parameter Exponential Distribution Based on Progres- sively Type-II Censored Data by Sajad Rostamian

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Spiked Dirichlet Process Priors for Gaussian Process Models by Terrance Savitsky, Marina Vannucci

“…We expand a framework for Bayesian variable selection for Gaussian process (GP) models by employing spiked Dirichlet process (DP) prior constructions over set partitions containing covariates. …”
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Novelty Detection in Autonomous Driving: A Generative Multi-Modal Sensor Fusion Approach by Hafsa Iqbal, Haleema Sadia, Abdulla Al-Kaff, Fernando Garcie

“…The MSF framework fuses both proprioceptive (wheel odometry) and exteroceptive (LiDAR point-clouds) sensory inputs. A novel 3-Dimensional Dynamic Variational Auto-Encoder (3D-DVAE) model is employed to learn attention-focused distributions from point-clouds in an unsupervised manner. …”
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On estimation of the quadratic hazard rate model parameters: Simulation and application by M. Nagy, A. H. Mansi, Moustafa N. Mousa, M. E. Moshref, N. Youns, M. M. M. Mansour

“…Asymptotic confidence intervals are derived, with a focus on the delta method. Bayesian inference is then performed under both MLE and MPS approaches using independent informative priors (normal and gamma) and both symmetric (squared error) and asymmetric (linear exponential) loss functions to obtain point estimates and highest posterior density credible intervals. …”
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Estimation of the scale parameter of gamma model in presence of outlier observations by M. E. Ghitany

“…This paper considers the Bayesian point estimation of the scale parameter for a two-parameter gamma life-testing model in presence of several outlier observations in the data. …”
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Asymptotic estimation for statistical models of continuous-time discrete martingales by Vaidotas Kanišauskas, Karolina Kanišauskienė

“… The paper deals with statistical experiments of the continuous-time discrete local martingales, including models of all types of point processes. The process of local density of the discrete local martingales is expressed by a stochastic exponent of the stochastic integral according to the compensated point measure. …”
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Epidemiological insights into canine rabies in Chennai: Trends, forecasting and One Health implications by Viswanathan Naveenkumar, Mangalanathan Vijaya Bharathi, Porteen Kannan, B.S. Pradeep Nag, Sureshkannan Sundaram, Nithya Quintoil Mohanadasse, Raghavendra G. Amachawadi, Muskan Dubey, Charley A. Cull, Chandan Shivamallu, Shiva Prasad Kollur, Ravindra P. Veeranna

“…Among the models tested, the Prophet model demonstrated the best predictive performance (RMSE: 1.88, MAE: 1.55, MAPE: 45.44 %, MASE: 3.52), outperforming the Generalized Additive Model (GAM), Bayesian Structural Time Series (BSTS) and Seasonal Trend decomposition using Loess combined with ARIMA (STL + ARIMA (0,0,2)). …”
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Optimizing the learning rate for adaptive estimation of neural encoding models. by Han-Lin Hsieh, Maryam M Shanechi

“…We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. …”
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A flexible Weibull geometric distribution with characterizations and its parameter estimation by Ahmadreza Zanboori, Ehsan Zanboori, Hamid Parvin, Mohammadreza Mahmoudi

“…The EM algorithm is used to compute the asymptotic variances and covariances of the parameters. Point estimators of the unknown parameters, under various symmetric and asymmetric loss functions, are obtained using the Bayesian framework and the Markov Chain Monte Carlo (MCMC) technique. …”
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