Digital twinJanus: One Agent, Two Roles for Digital Twin Construction and Network OrchestrationarXiv API — полнотекстовый поиск "digital twin" · 3dModellingStochastic MPC robust to errors in disturbance statisticsarXiv — Systems and Control (eess.SY) · 3dModellingРоман Венедиктов («Эмерджентные мультиагентные системы»): «Сегодня сам факт использования ИИ стал обычной частью корпоративной ИТ-среды»spbIT · 3dDigital twinA High-Fidelity Cardiac Digital Twin for Assessing Rate-Dependent Responses: A Comparative Multi-scale Study of TT2 and Tomek Models in Stratified 3D VentriclesarXiv API — полнотекстовый поиск "digital twin" · 3dForecastingAdaptive clustering for robust distributed MPC of coupled multi-agent systemsarXiv — Systems and Control (eess.SY) · 3dForecastingNeural approximation of NMPC without expert demonstrationsarXiv — Systems and Control (eess.SY) · 3dAssets & dataAn operational model for a trusted data space in vocational educationarXiv — Computers and Society (cs.CY) · 3dModellingАгентная система для тех, кто вкатывается: собираем агента поддержки от одного файла до Temporal, саги и circuit breakerХабр · 4dDigital twinOnline digital twin: data assimilation and control in a mean-field formulationarXiv — Systems and Control (eess.SY) · 4dDigital twinSurvey of digital twin networks for 6G: architecture, technologies and AI controlarXiv — Systems and Control (eess.SY) · 4dDigital twin5G NR neural receiver trained on corridor digital twin dataarXiv API — полнотекстовый поиск "digital twin" · 4dForecastingSampling-based MPC unified as a single sequential Monte Carlo algorithmarXiv — Systems and Control (eess.SY) · 4d
Evaluating workforce training programs with tax records and experimental benchmarks
US & West ·
Using anonymized income tax records for all US adults from 1999 to 2025, the study estimates earnings effects of workforce training programs, predicting counterfactuals with machine learning from work histories, demographics and location. Estimated bias is benchmarked against 37 randomized controlled trials.
Why it matters
It illustrates how large administrative data and learned models can scale program-effect estimation while being calibrated against experimental benchmarks.
Next-generation wireless networks are increasingly large-scale, heterogeneous, and dynamic, posing significant challenges to network modeling and control. Digital twins offer a promising solution, but existing approaches typically rely on static models and decouple twin construction from network…
Cardiac digital twins (CDTs) provide a computational platform for personalized cardiac modeling, but their predictive behavior depends strongly on the selected ionic model and the representation of transmural electrophysiological heterogeneity.
