Digital twinDe-Risking Robotic Welding for In-Space Metal Joining Through Physics-Grounded Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · 22hModellingSequential Learning-Based Physics-Informed Neural Network Modeling for Parameter Estimation on a Power ConverterarXiv — Systems and Control (eess.SY) · yesterdayModellingAdaptive Handling of Deadline Misses via Stochastic MPCarXiv — Systems and Control (eess.SY) · 2dModellingInstitutionalizing Trust in Data Exchange: Trust-Anchor Model of the Data Credit Guarantee Organization and Its Simulation-Based ComparisonarXiv — Computers and Society (cs.CY) · 2dDigital twinDigital Twin-Conditioned RSS-Fingerprint Localization in Cell-Free Millimeter-Wave NetworksarXiv API — полнотекстовый поиск "digital twin" · yesterdayModellingAI уже делает инженеров хуже? Как агентная разработка выращивает технологический зоопаркХабр · yesterdayDigital twinFeasibility of a Patient-Specific Digital Twin for Ventriculoperitoneal Shunt Trajectory PlanningarXiv API — полнотекстовый поиск "digital twin" · 2dModellingBayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic ModelsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 2dDigital twinDecision-Making in Digital Twins: Optimization, Control, and LearningarXiv — Systems and Control (eess.SY) · 2dDigital twinBALLAST: Physics-Aware Moving Target Defense for Industrial Control Systems Using a Digital Twin Safety OraclearXiv — Systems and Control (eess.SY) · 2dDigital twinОпубликованы итоги форсайт-сессии «Будущее безопасности киберфизических систем в России. Перспективы и векторы развития»spbIT · 2dDigital twinProbabilistic Physics Digital Twin for Human-Robot InteractionarXiv API — полнотекстовый поиск "digital twin" · 2d
Neural Network-Based Parameter Estimation for a Labour Market ABM
US & West ·
This study applies a state-of-the-art simulation-based inference framework with neural networks to estimate parameters of a labour market agent-based model. The model is based on job transition networks and is initialized with synthetic and real U.S. labour market data. The approach addresses computational constraints in exploring the parameter space.
Why it matters
The method is important for practical use of agent-based models in decision support, as it enables calibration of complex models on real data.
Original headline
Neural Network-Based Parameter Estimation of a Labour Market Agent-Based Model
arXiv:2610.20041v1 Announce Type: cross Abstract: A staged physics-informed neural network (PINN) is proposed for identifying the inductance, capacitance and parasitic resistances of a DC buck converter from time-domain data.
arXiv:2610.18361v1 Announce Type: new Abstract: Real-time control systems may experience sporadic computational overloads that cause controller executions to overrun their expected deadlines, affecting the timely update of control inputs.
arXiv:2610.18400v1 Announce Type: new Abstract: Data trading markets that span industries and regions are expanding, but the implicit trust that supports data use within an organization does not carry over to cross-domain exchange.
