Saved in:
| Main Authors: | Fotias, Sofianos Panagiotis, Gaganis, Vassilis |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.02405 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025)
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025)
Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop
by: Picerno, Mario, et al.
Published: (2023)
by: Picerno, Mario, et al.
Published: (2023)
Verifying Closed-Loop Contractivity of Learning-Based Controllers via Partitioning
by: Davydov, Alexander
Published: (2025)
by: Davydov, Alexander
Published: (2025)
Closed-Loop Transformers: Autoregressive Modeling as Iterative Latent Equilibrium
by: Jafari, Akbar Anbar, et al.
Published: (2025)
by: Jafari, Akbar Anbar, et al.
Published: (2025)
MADE: Benchmark Environments for Closed-Loop Materials Discovery
by: Malik, Shreshth A, et al.
Published: (2026)
by: Malik, Shreshth A, et al.
Published: (2026)
Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control
by: Mole, Andrew, et al.
Published: (2025)
by: Mole, Andrew, et al.
Published: (2025)
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
by: Alles, Marvin, et al.
Published: (2024)
by: Alles, Marvin, et al.
Published: (2024)
Neural ODE and SDE Models for Adaptation and Planning in Model-Based Reinforcement Learning
by: Han, Chao, et al.
Published: (2026)
by: Han, Chao, et al.
Published: (2026)
Safe and Stable Closed-Loop Learning for Neural-Network-Supported Model Predictive Control
by: Hirt, Sebastian, et al.
Published: (2024)
by: Hirt, Sebastian, et al.
Published: (2024)
Closed-Loop Neural Operator-Based Observer of Traffic Density
by: Harting, Alice, et al.
Published: (2025)
by: Harting, Alice, et al.
Published: (2025)
TwinLoop: Simulation-in-the-Loop Digital Twins for Online Multi-Agent Reinforcement Learning
by: Zhang, Nan, et al.
Published: (2026)
by: Zhang, Nan, et al.
Published: (2026)
High-Dimensional Surrogate Modeling for Closed-Loop Learning of Neural-Network-Parameterized Model Predictive Control
by: Hirt, Sebastian, et al.
Published: (2025)
by: Hirt, Sebastian, et al.
Published: (2025)
A Hierarchical Surrogate Model for Efficient Multi-Task Parameter Learning in Closed-Loop Control
by: Hirt, Sebastian, et al.
Published: (2025)
by: Hirt, Sebastian, et al.
Published: (2025)
Deep Learning Framework for History Matching CO2 Storage with 4D Seismic and Monitoring Well Data
by: Wang, Nanzhe, et al.
Published: (2024)
by: Wang, Nanzhe, et al.
Published: (2024)
Adaptive Outer-Loop Control of Quadrotors via Reinforcement Learning
by: Saj, Vishnu, et al.
Published: (2026)
by: Saj, Vishnu, et al.
Published: (2026)
Discovering Closed-Loop Failures of Vision-Based Controllers via Reachability Analysis
by: Chakraborty, Kaustav, et al.
Published: (2022)
by: Chakraborty, Kaustav, et al.
Published: (2022)
Heat Death of Generative Models in Closed-Loop Learning
by: Marchi, Matteo, et al.
Published: (2024)
by: Marchi, Matteo, et al.
Published: (2024)
Revealing the Challenges of Sim-to-Real Transfer in Model-Based Reinforcement Learning via Latent Space Modeling
by: Lin, Zhilin, et al.
Published: (2025)
by: Lin, Zhilin, et al.
Published: (2025)
Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control
by: Xiao, Maxiu, et al.
Published: (2025)
by: Xiao, Maxiu, et al.
Published: (2025)
Deep Reinforcement Learning Behavioral Mode Switching Using Optimal Control Based on a Latent Space Objective
by: Remman, Sindre Benjamin, et al.
Published: (2024)
by: Remman, Sindre Benjamin, et al.
Published: (2024)
Deep Reinforcement Learning-Based DRAM Equalizer Parameter Optimization Using Latent Representations
by: Usama, Muhammad, et al.
Published: (2025)
by: Usama, Muhammad, et al.
Published: (2025)
Model-Based Reinforcement Learning for Control under Time-Varying Dynamics
by: Iten, Klemens, et al.
Published: (2026)
by: Iten, Klemens, et al.
Published: (2026)
Closing the Loop: Coordinating Inventory and Recommendation via Deep Reinforcement Learning on Multiple Timescales
by: Jiang, Jinyang, et al.
Published: (2025)
by: Jiang, Jinyang, et al.
Published: (2025)
LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models
by: Park, Taekhyun, et al.
Published: (2026)
by: Park, Taekhyun, et al.
Published: (2026)
On Rollouts in Model-Based Reinforcement Learning
by: Frauenknecht, Bernd, et al.
Published: (2025)
by: Frauenknecht, Bernd, et al.
Published: (2025)
Model-Based Reinforcement Learning for Atari
by: Kaiser, Lukasz, et al.
Published: (2019)
by: Kaiser, Lukasz, et al.
Published: (2019)
Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees
by: Junnarkar, Neelay, et al.
Published: (2024)
by: Junnarkar, Neelay, et al.
Published: (2024)
Comparing Traditional and Reinforcement-Learning Methods for Energy Storage Control
by: Ginzburg, Elinor, et al.
Published: (2025)
by: Ginzburg, Elinor, et al.
Published: (2025)
medDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support
by: Xu, Qianyi, et al.
Published: (2025)
by: Xu, Qianyi, et al.
Published: (2025)
Economic Battery Storage Dispatch with Deep Reinforcement Learning from Rule-Based Demonstrations
by: Sage, Manuel, et al.
Published: (2025)
by: Sage, Manuel, et al.
Published: (2025)
maxVSTAR: Maximally Adaptive Vision-Guided CSI Sensing with Closed-Loop Edge Model Adaptation for Robust Human Activity Recognition
by: Liu, Kexing
Published: (2025)
by: Liu, Kexing
Published: (2025)
Power Grid Control with Graph-Based Distributed Reinforcement Learning
by: Fabrizio, Carlo, et al.
Published: (2025)
by: Fabrizio, Carlo, et al.
Published: (2025)
Temporal Basis Function Models for Closed-Loop Neural Stimulation
by: Bryan, Matthew J., et al.
Published: (2025)
by: Bryan, Matthew J., et al.
Published: (2025)
Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models
by: Zhang, Zhejun, et al.
Published: (2024)
by: Zhang, Zhejun, et al.
Published: (2024)
Model-Based Transfer Learning for Contextual Reinforcement Learning
by: Cho, Jung-Hoon, et al.
Published: (2024)
by: Cho, Jung-Hoon, et al.
Published: (2024)
Learning Dynamics of RNNs in Closed-Loop Environments
by: Ger, Yoav, et al.
Published: (2025)
by: Ger, Yoav, et al.
Published: (2025)
Grammarization-Based Grasping with Deep Multi-Autoencoder Latent Space Exploration by Reinforcement Learning Agent
by: Askianakis, Leonidas
Published: (2024)
by: Askianakis, Leonidas
Published: (2024)
Latent Variable Modeling in Multi-Agent Reinforcement Learning via Expectation-Maximization for UAV-Based Wildlife Protection
by: Taghavi, Mazyar, et al.
Published: (2025)
by: Taghavi, Mazyar, et al.
Published: (2025)
Time-Varying Constraint-Aware Reinforcement Learning for Energy Storage Control
by: Jeong, Jaeik, et al.
Published: (2024)
by: Jeong, Jaeik, et al.
Published: (2024)
Tools in the Loop: Quantifying Uncertainty of LLM Question Answering Systems That Use Tools
by: Lymperopoulos, Panagiotis, et al.
Published: (2025)
by: Lymperopoulos, Panagiotis, et al.
Published: (2025)
Similar Items
-
Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025) -
Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop
by: Picerno, Mario, et al.
Published: (2023) -
Verifying Closed-Loop Contractivity of Learning-Based Controllers via Partitioning
by: Davydov, Alexander
Published: (2025) -
Closed-Loop Transformers: Autoregressive Modeling as Iterative Latent Equilibrium
by: Jafari, Akbar Anbar, et al.
Published: (2025) -
MADE: Benchmark Environments for Closed-Loop Materials Discovery
by: Malik, Shreshth A, et al.
Published: (2026)