Copertina

Variational Digital Twins

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Burnett, Logan A., Nabila, Umme Mahbuba, Radaideh, Majdi I.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Systems and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning
di: Nabila, Umme Mahbuba, et al.
Pubblicazione: (2026)

Nuclear Microreactor Control with Deep Reinforcement Learning
di: Tunkle, Leo, et al.
Pubblicazione: (2025)

Multistep Criticality Search and Power Shaping in Microreactors with Reinforcement Learning
di: Radaideh, Majdi I., et al.
Pubblicazione: (2024)

Multifidelity Surrogate Modeling of Depressurized Loss of Forced Cooling in High-temperature Gas Reactors
di: Eaheart, Meredith, et al.
Pubblicazione: (2026)

Constructing and Evaluating Digital Twins: An Intelligent Framework for DT Development
di: Ma, Longfei, et al.
Pubblicazione: (2024)

Generative Flow Networks for Model Adaptation in Digital Twins of Natural Systems
di: Archambault, Pascal, et al.
Pubblicazione: (2026)

Control of Medical Digital Twins with Artificial Neural Networks
di: Böttcher, Lucas, et al.
Pubblicazione: (2024)

Sparse Attention-driven Quality Prediction for Production Process Optimization in Digital Twins
di: Yin, Yanlei, et al.
Pubblicazione: (2024)

Real-Time AI-Driven Milling Digital Twin Towards Extreme Low-Latency
di: Liu, Wenyi, et al.
Pubblicazione: (2025)

Equation-Free Digital Twins for Nonlinear Structural Dynamics
di: Abaei, Mohammad Mahdi, et al.
Pubblicazione: (2026)

Physics-Embedded Neural ODEs for Sim2Real Edge Digital Twins of Hybrid Power Electronics Systems
di: Zheng, Jialin, et al.
Pubblicazione: (2025)

An LLM-Based Digital Twin for Optimizing Human-in-the Loop Systems
di: Yang, Hanqing, et al.
Pubblicazione: (2024)

Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
di: Tao, Zhenyu, et al.
Pubblicazione: (2024)

A Digital Twin for Diesel Engines: Operator-infused Physics-Informed Neural Networks with Transfer Learning for Engine Health Monitoring
di: Nath, Kamaljyoti, et al.
Pubblicazione: (2024)

Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation
di: Internò, Christian, et al.
Pubblicazione: (2025)

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework
di: Lin, Yu-Zheng, et al.
Pubblicazione: (2024)

Digital Twin-based Out-of-Distribution Detection in Autonomous Vessels
di: Isaku, Erblin, et al.
Pubblicazione: (2025)

Optimizing Wireless Resource Management and Synchronization in Digital Twin Networks
di: Yu, Hanzhi, et al.
Pubblicazione: (2025)

Automatic dimensionality reduction of Twin-in-the-Loop Observers
di: Delcaro, Giacomo, et al.
Pubblicazione: (2024)

Digital Twin Assisted Deep Reinforcement Learning for Online Admission Control in Sliced Network
di: Tao, Zhenyu, et al.
Pubblicazione: (2023)

Review on Fault Diagnosis and Fault-Tolerant Control Scheme for Robotic Manipulators: Recent Advances in AI, Machine Learning, and Digital Twin
di: Quamar, Md Muzakkir, et al.
Pubblicazione: (2024)

Learn for Variation: Variationally Guided AAV Trajectory Learning in Differentiable Environments
di: Wang, Xiucheng, et al.
Pubblicazione: (2026)

VoI-Driven Joint Optimization of Control and Communication in Vehicular Digital Twin Network
di: Lei, Lei, et al.
Pubblicazione: (2025)

Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks
di: Yu, Hanzhi, et al.
Pubblicazione: (2026)

SCoTT: Strategic Chain-of-Thought Tasking for Wireless-Aware Robot Navigation in Digital Twins
di: Djuhera, Aladin, et al.
Pubblicazione: (2024)

Sustainability of Data Center Digital Twins with Reinforcement Learning
di: Sarkar, Soumyendu, et al.
Pubblicazione: (2024)

Stability Enhanced Gaussian Process Variational Autoencoders
di: Richardson, Carl R., et al.
Pubblicazione: (2026)

Real-Time Decision-Making for Digital Twin in Additive Manufacturing with Model Predictive Control using Time-Series Deep Neural Networks
di: Chen, Yi-Ping, et al.
Pubblicazione: (2025)

On the Impact of Language Nuances on Sentiment Analysis with Large Language Models: Paraphrasing, Sarcasm, and Emojis
di: Bhargava, Naman, et al.
Pubblicazione: (2025)

Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges
di: Cheng, Nan, et al.
Pubblicazione: (2024)

Digital Twin Synchronization: Bridging the Sim-RL Agent to a Real-Time Robotic Additive Manufacturing Control
di: Ali, Matsive, et al.
Pubblicazione: (2025)

Weighted Flow Matching and Physics-Informed Nonlinear Filtering for Parameter Estimation in Digital Twins
di: Yanik, Yasar, et al.
Pubblicazione: (2026)

Deep Koopman-based Control of Quality Variation in Multistage Manufacturing Systems
di: Chen, Zhiyi, et al.
Pubblicazione: (2024)

Deep Generative and Discriminative Digital Twin endowed with Variational Autoencoder for Unsupervised Predictive Thermal Condition Monitoring of Physical Robots in Industry 6.0 and Society 6.0
di: Kaigom, Eric Guiffo
Pubblicazione: (2025)

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning
di: Liu, Ruohong, et al.
Pubblicazione: (2025)

Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders
di: Sundsgaard, Konrad, et al.
Pubblicazione: (2025)

Towards Trustworthy 6G Network Digital Twins: A Framework for Validating Counterfactual What-If Analysis in Edge Computing Resources
di: Agudelo, Julian Jimenez, et al.
Pubblicazione: (2026)

High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications
di: Burnett, Logan A., et al.
Pubblicazione: (2026)

Data-Based In-Cylinder Pressure Model with Cyclic Variations for Combustion Control: A RCCI Engine Application
di: Vlaswinkel, Maarten, et al.
Pubblicazione: (2024)

Optimizing Digital Therapeutic Interventions: Online Learning under Endogenous Adherence
di: Pulick, Eric, et al.
Pubblicazione: (2026)