Saved in:
| Main Author: | Eldin, Ahmed Gamal |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.18909 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Artifacts Are Not Noise: Embodied Resonance and the 70% Signal Loss in Conventional EEG
by: Eldin, Ahmed Gamal
Published: (2025)
by: Eldin, Ahmed Gamal
Published: (2025)
Beyond Prediction: Interval Neural Networks for Uncertainty-Aware System Identification
by: Ferah, Mehmet Ali, et al.
Published: (2026)
by: Ferah, Mehmet Ali, et al.
Published: (2026)
Smart Exploration in Reinforcement Learning using Bounded Uncertainty Models
by: van Hulst, J. S., et al.
Published: (2025)
by: van Hulst, J. S., et al.
Published: (2025)
Dyna-Style Reinforcement Learning Modeling and Control of Non-linear Dynamics
by: Abdelsalam, Karim, et al.
Published: (2025)
by: Abdelsalam, Karim, et al.
Published: (2025)
Bounded Exploration with World Model Uncertainty in Soft Actor-Critic Reinforcement Learning Algorithm
by: Qiao, Ting, et al.
Published: (2024)
by: Qiao, Ting, et al.
Published: (2024)
CLT-Optimal Parameter Error Bounds for Linear System Identification
by: Zhou, Yichen, et al.
Published: (2026)
by: Zhou, Yichen, et al.
Published: (2026)
Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics
by: Frauenknecht, Bernd, et al.
Published: (2026)
by: Frauenknecht, Bernd, et al.
Published: (2026)
Smart Predict-then-Optimize Method with Dependent Data: Risk Bounds and Calibration of Autoregression
by: Liu, Jixian, et al.
Published: (2024)
by: Liu, Jixian, et al.
Published: (2024)
Non-Asymptotic Bounds for Closed-Loop Identification of Unstable Nonlinear Stochastic Systems
by: Siriya, Seth, et al.
Published: (2024)
by: Siriya, Seth, et al.
Published: (2024)
Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
by: Sattar, Yahya, et al.
Published: (2021)
by: Sattar, Yahya, et al.
Published: (2021)
LUCID: Learning-Enabled Uncertainty-Aware Certification of Stochastic Dynamical Systems
by: Casablanca, Ernesto, et al.
Published: (2025)
by: Casablanca, Ernesto, et al.
Published: (2025)
Discrete-time Contraction-based Control of Nonlinear Systems with Parametric Uncertainties using Neural Networks
by: Wei, Lai, et al.
Published: (2021)
by: Wei, Lai, et al.
Published: (2021)
Sample Complexity Bounds for Linear System Identification from a Finite Set
by: Chatzikiriakos, Nicolas, et al.
Published: (2024)
by: Chatzikiriakos, Nicolas, et al.
Published: (2024)
Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control
by: Saviolo, Alessandro, et al.
Published: (2022)
by: Saviolo, Alessandro, et al.
Published: (2022)
Improved Robustness of Deep Reinforcement Learning for Control of Time-Varying Systems by Bounded Extremum Seeking
by: Saxena, Shaifalee, et al.
Published: (2025)
by: Saxena, Shaifalee, et al.
Published: (2025)
Achieving $\widetilde{O}(1/ε)$ Sample Complexity for Bilinear Systems Identification under Bounded Noises
by: Yi, Hongyu, et al.
Published: (2026)
by: Yi, Hongyu, et al.
Published: (2026)
Interpolation Conditions for Data Consistency and Prediction in Noisy Linear Systems
by: Vanelli, Martina, et al.
Published: (2025)
by: Vanelli, Martina, et al.
Published: (2025)
Physics-Constrained Learning for PDE Systems with Uncertainty Quantified Port-Hamiltonian Models
by: Tan, Kaiyuan, et al.
Published: (2024)
by: Tan, Kaiyuan, et al.
Published: (2024)
Data-driven Kinematic Modeling in Soft Robots: System Identification and Uncertainty Quantification
by: Jiang, Zhanhong, et al.
Published: (2025)
by: Jiang, Zhanhong, et al.
Published: (2025)
Improved Scalable Lipschitz Bounds for Deep Neural Networks
by: Syed, Usman, et al.
Published: (2025)
by: Syed, Usman, et al.
Published: (2025)
Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems
by: Chakrabarti, Ananda, et al.
Published: (2026)
by: Chakrabarti, Ananda, et al.
Published: (2026)
Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and Classification Tasks
by: Lützow, Laura, et al.
Published: (2025)
by: Lützow, Laura, et al.
Published: (2025)
Dual Control of Linear Systems from Bilinear Observations with Belief Space Model Predictive Control
by: Cao, Daniel, et al.
Published: (2026)
by: Cao, Daniel, et al.
Published: (2026)
Wiener Chaos in Kernel Regression: Towards Untangling Aleatoric and Epistemic Uncertainty
by: Faulwasser, T., et al.
Published: (2023)
by: Faulwasser, T., et al.
Published: (2023)
A Concentration Bound for TD(0) with Function Approximation
by: Chandak, Siddharth, et al.
Published: (2023)
by: Chandak, Siddharth, et al.
Published: (2023)
On Robust Reinforcement Learning with Lipschitz-Bounded Policy Networks
by: Barbara, Nicholas H., et al.
Published: (2024)
by: Barbara, Nicholas H., et al.
Published: (2024)
Hierarchical Upper Confidence Bounds for Constrained Online Learning
by: Baheri, Ali
Published: (2024)
by: Baheri, Ali
Published: (2024)
Learning to Route Electric Trucks Under Operational Uncertainty
by: Orfanoudakis, Stavros, et al.
Published: (2026)
by: Orfanoudakis, Stavros, et al.
Published: (2026)
A Dynamic Recurrent Adjacency Memory Network for Mixed-Generation Power System Stability Forecasting
by: Ooi, Guang An, et al.
Published: (2025)
by: Ooi, Guang An, et al.
Published: (2025)
Data-Driven Prediction and Control of Hammerstein-Wiener Systems with Implicit Gaussian Processes
by: Yin, Mingzhou, et al.
Published: (2025)
by: Yin, Mingzhou, et al.
Published: (2025)
High-Probability Bounds for SGD under the Polyak-Lojasiewicz Condition with Markovian Noise
by: Kar, Avik, et al.
Published: (2026)
by: Kar, Avik, et al.
Published: (2026)
Uncertainty Modelling and Robust Observer Synthesis using the Koopman Operator
by: Dahdah, Steven, et al.
Published: (2024)
by: Dahdah, Steven, et al.
Published: (2024)
Verifiable Error Bounds for Physics-Informed Neural KKL Observers
by: Berin-Costain, Hannah, et al.
Published: (2026)
by: Berin-Costain, Hannah, et al.
Published: (2026)
Learning Surrogate LPV State-Space Models with Uncertainty Quantification
by: Olucha, E. Javier, et al.
Published: (2026)
by: Olucha, E. Javier, et al.
Published: (2026)
Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets
by: Solanki, Prashant, et al.
Published: (2025)
by: Solanki, Prashant, et al.
Published: (2025)
Certifying Guidance & Control Networks: Uncertainty Propagation to an Event Manifold
by: Origer, Sebastien, et al.
Published: (2024)
by: Origer, Sebastien, et al.
Published: (2024)
MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models
by: Yan, Jiaqi, et al.
Published: (2024)
by: Yan, Jiaqi, et al.
Published: (2024)
Learning Locally Interacting Discrete Dynamical Systems: Towards Data-Efficient and Scalable Prediction
by: Kang, Beomseok, et al.
Published: (2024)
by: Kang, Beomseok, et al.
Published: (2024)
Diffusion-assisted Model Predictive Control Optimization for Power System Real-Time Operation
by: Xu, Linna, et al.
Published: (2025)
by: Xu, Linna, et al.
Published: (2025)
A Robust Task-Level Control Architecture for Learned Dynamical Systems
by: Pathak, Eshika, et al.
Published: (2025)
by: Pathak, Eshika, et al.
Published: (2025)
Similar Items
-
Artifacts Are Not Noise: Embodied Resonance and the 70% Signal Loss in Conventional EEG
by: Eldin, Ahmed Gamal
Published: (2025) -
Beyond Prediction: Interval Neural Networks for Uncertainty-Aware System Identification
by: Ferah, Mehmet Ali, et al.
Published: (2026) -
Smart Exploration in Reinforcement Learning using Bounded Uncertainty Models
by: van Hulst, J. S., et al.
Published: (2025) -
Dyna-Style Reinforcement Learning Modeling and Control of Non-linear Dynamics
by: Abdelsalam, Karim, et al.
Published: (2025) -
Bounded Exploration with World Model Uncertainty in Soft Actor-Critic Reinforcement Learning Algorithm
by: Qiao, Ting, et al.
Published: (2024)