Damping profile learning for human-robot collaboration using Bayesian optimization with a task success rate model by Liem Duc TRAN, Tasuku YAMAWAKI, Masahito YASHIMA

“…This study proposes a novel approach to enhance the performance of human-robot collaboration by adapting the damping profile used in admittance control. The proposed method employs Bayesian optimization to appropriately adjust the damping profile, even when the cost function and unknown constraints are computationally expensive to evaluate, which is a common scenario in human-robot collaboration. …”
Get full text

Equation of State Independent Determination on the Radius of a 1.4 M⊙ Neutron Star Using Mass–Radius Measurements by Chun Huang

Get full text

Deterministic form-position deflectometric measurement of monolithic multi-freeform optical structures via Bayesian multisensor fusion by Wei Lang, Xiangchao Zhang, Yunuo Chen, Ting Chen, Peide Yang, Min Xu, Xiangqian Jiang

“…Finally, a geometric-constraint-based registration method was developed to evaluate the form-position quality of freeform surfaces. …”
Get full text

Efficient Trans-Dimensional Bayesian Inversion of C-Response Data from Geomagnetic Observatory and Satellite Magnetic Data by Rongwen Guo, Shengqi Tian, Jianxin Liu, Yi-an Cui, Chuanghua Cao

“…This method typically requires the model parameterization knowledge a priori (e.g., based on personal preference) without uncertainty estimation. …”
Get full text

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model. by Rui Meng, Kristofer E Bouchard

“…Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. …”
Get full text

From Existing and New Nuclear and Astrophysical Constraints to Stringent Limits on the Equation of State of Neutron-Rich Dense Matter by Hauke Koehn, Henrik Rose, Peter T. H. Pang, Rahul Somasundaram, Brendan T. Reed, Ingo Tews, Adrian Abac, Oleg Komoltsev, Nina Kunert, Aleksi Kurkela, Michael W. Coughlin, Brian F. Healy, Tim Dietrich

“…For this purpose, we present a broad compendium of different constraints and apply them individually to a large set of EOS candidates within a Bayesian framework. …”
Get full text

A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems by Cornelius Rüther, Julia Rieck

“…<i>Methods</i>: To solve the MDPDPTWHV, we present a Grouping Genetic Algorithm (GGA) framework with several operators and population management variants. …”
Get full text

Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach by Marko Martinović, Kristian Dokic, Dalibor Pudić

“…In this study, multiple machine learning models, encompassing both ensemble-based and single-model approaches, were applied to data from the Community Innovation Survey. Methods included random forests, gradient boosting frameworks, support vector machines, neural networks, and logistic regression, each with hyperparameters optimized through Bayesian search routines and evaluated using corrected cross-validation techniques. …”
Get full text

Objective Framework for Bayesian Inference in Multicomponent Pareto Stress–Strength Model Under an Adaptive Progressive Type-II Censoring Scheme by Young Eun Jeon, Yongku Kim, Jung-In Seo

“…For instance, in the likelihood-based method, the asymptotic variance–covariance matrix may not exist due to certain constraints. …”
Get full text

Model-independent Determination of the Tidal Deformability of a 1.4 M⊙ Neutron Star from Gravitational-wave Measurements by Chun Huang

Get full text

Enhancing catch-based stock assessment in data-limited fisheries with proxy CPUE indicators in the Yellow Sea by Kun Wang, Qi Li, Chongliang Zhang, Binduo Xu, Yiping Ren

“…These indicators were incorporated into a Bayesian state-space Schaefer surplus production model (BSM) and their performance was compared to catch-only methods (CMSY) across key evaluation criteria, including robustness of estimation, reliability in retrospective analyses, and performance when encountering catch observation errors. …”
Get full text

Shale Fracture Static Stability Evaluation Method Based on 3D Discrete Fracture Model: A Case Study on the Luzhou Area in Southern Sichuan Basin, SW China by Ruhua Zhang, Cheng Yin, Jianping Huang

“…In this article, seismic geometric attributes were calculated, and fracture seismic facies was established by means of the Bayesian probabilistic cluster analysis method. Then, 3D discrete fracture modeling under the constraint of fracture seismic facies was performed to establish a discrete fracture model. …”
Get full text

Safety Risk Assessment of Jacking Renovation Construction for Aging Bridges Based on DBN and Fuzzy Set Theory by Yanhui Ge, Yang You

“…Addressing the limitations of traditional risk assessment methods in handling dynamic changes and data scarcity, this study proposes a safety risk assessment approach based on dynamic Bayesian networks (DBN) and fuzzy set theory (FST). …”
Get full text

Characterizing Offshore Freshened Groundwater Salinity Patterns Using Trans‐Dimensional Bayesian Inversion of Controlled Source Electromagnetic Data: A Case Study From the Canterbu... by Zahra Faghih, Amir Haroon, Marion Jegen, Romina Gehrmann, Katrin Schwalenberg, Aaron Micallef, Jan Dettmer, Christian Berndt, Joshu Mountjoy, Bradley A. Weymer

“…Our findings highlight the potential of Bayesian inversion to enhance our understanding of OFG systems and provide uncertainty constraints for hydrogeological modeling, thereby contributing to sustainable water resource development.…”
Get full text

Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes by Yoav Rotman, Luis Welbanks, Michael R. Line, Peter McGill, Michael Radica, Matthew C. Nixon

Get full text

Analyzing Chemical Decay in Environmental Nanomaterials Using Gamma Distribution with Hybrid Censoring Scheme by Hanan Haj Ahmad, Dina A. Ramadan, Mohamed Aboshady

“…We employ maximum likelihood estimation (MLE) and Bayesian methods to estimate the model’s parameters, consequently estimating the reliability and hazard functions. …”
Get full text

Advancing Cosmological Parameter Estimation and Hubble Parameter Reconstruction with Long Short-term Memory and Efficient Kolmogorov–Arnold Networks by Jiaxing Cui, Marek Biesiada, Ao Liu, Cuihong Wen, Tonghua Liu, Jieci Wang

Get full text

Physics-Informed Neural Networks with Unknown Partial Differential Equations: An Application in Multivariate Time Series by Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Ali Mohammad-Djafari

“…In this work, we introduce methods to automatically select PDEs from historical data in a parametric family. …”
Get full text

A Hierarchical Evolutionary Search Framework with Manifold Learning for Powertrain Optimization of Flying Vehicles by Chenghao Lyu, Nuo Lei, Chaoyi Chen, Hao Zhang

“…The co-optimization aims to minimize fuel consumption, battery state-of-health (SOH) degradation, and manufacturing costs while satisfying dynamic and energy management constraints. Evaluated using representative HEVTOL duty cycles, the HM-BEO demonstrates significant improvements in optimization efficiency and solution quality compared to conventional methods. …”
Get full text

3D Localization of FRB 20190425A for Its Potential Host Galaxy and Implications by Da-Chun Qiang, Zhi-Qiang You, Sheng Yang, Zong-Hong Zhu, Ting-Wan Chen

Get full text