:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hu, Songqiao, Liu, Zeyi, He, Xiao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Systems and Control
Online Access:	https://arxiv.org/abs/2506.08063
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Performance-bounded Online Ensemble Learning Method Based on Multi-armed bandits and Its Applications in Real-time Safety Assessment
by: Hu, Songqiao, et al.
Published: (2025)

SafeLink: Safety-Critical Control Under Dynamic and Irregular Unsafe Regions
by: Hu, Songqiao, et al.
Published: (2025)

Asymmetric Adaptation-based Real-time Fault Diagnosis Under Transitional Operating Conditions
by: Zhao, Hongshuo, et al.
Published: (2026)

LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction
by: Liu, Jun, et al.
Published: (2024)

VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer
by: Hu, Songqiao, et al.
Published: (2025)

Adapting to Change: A Comparison of Continual and Transfer Learning for Modeling Building Thermal Dynamics under Concept Drifts
by: Raisch, Fabian, et al.
Published: (2025)

Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification
by: Liu, Jun, et al.
Published: (2023)

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks
by: Ata, Baris, et al.
Published: (2023)

Awesome-OL: An Extensible Toolkit for Online Learning
by: Liu, Zeyi, et al.
Published: (2025)

Wave-RVFL: A Randomized Neural Network Based on Wave Loss Function
by: Sajid, M., et al.
Published: (2024)

Verification of Neural Control Barrier Functions with Symbolic Derivative Bounds Propagation
by: Hu, Hanjiang, et al.
Published: (2024)

Improved Scalable Lipschitz Bounds for Deep Neural Networks
by: Syed, Usman, et al.
Published: (2025)

Constructive Lyapunov Functions via Topology-Preserving Neural Networks
by: Oh, Jaehong
Published: (2025)

Modeling Electromagnetic Navigation Systems for Medical Applications using Random Forests and Artificial Neural Networks
by: Yu, Ruoxi, et al.
Published: (2019)

Verification-Aided Learning of Neural Network Barrier Functions with Termination Guarantees
by: Chen, Shaoru, et al.
Published: (2024)

Exploring Lightweight Federated Learning for Distributed Load Forecasting
by: Duttagupta, Abhishek, et al.
Published: (2024)

Real-Time Safe Control of Neural Network Dynamic Models with Sound Approximation
by: Hu, Hanjiang, et al.
Published: (2024)

Formally Verified Physics-Informed Neural Control Lyapunov Functions
by: Liu, Jun, et al.
Published: (2024)

Learning Performance-Oriented Control Barrier Functions Under Complex Safety Constraints and Limited Actuation
by: Manda, Lakshmideepakreddy, et al.
Published: (2024)

Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
by: Ajeyemi, Damola, et al.
Published: (2025)

Function Gradient Approximation with Random Shallow ReLU Networks with Control Applications
by: Lamperski, Andrew, et al.
Published: (2024)

Stability and Performance Analysis of Discrete-Time ReLU Recurrent Neural Networks
by: Noori, Sahel Vahedi, et al.
Published: (2024)

Peer-to-Peer Learning Dynamics of Wide Neural Networks
by: Chaudhari, Shreyas, et al.
Published: (2024)

Structured Cooperative Multi-Agent Reinforcement Learning: a Bayesian Network Perspective
by: Syed, Shahbaz P Qadri, et al.
Published: (2025)

A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning
by: Gokhale, Anand, et al.
Published: (2026)

Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification
by: Alsmeier, Hendrik, et al.
Published: (2025)

Integrating Lagrangian Neural Networks into the Dyna Framework for Reinforcement Learning
by: Das, Shreya, et al.
Published: (2026)

Safe Neural Control for Non-Affine Control Systems with Differentiable Control Barrier Functions
by: Xiao, Wei, et al.
Published: (2023)

A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN
by: Li, Aohan, et al.
Published: (2022)

Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
by: Serry, Mohamed, et al.
Published: (2026)

A Graph Neural Network with Auxiliary Task Learning for Missing PMU Data Reconstruction
by: Li, Bo, et al.
Published: (2025)

Learning and Current Prediction of PMSM Drive via Differential Neural Networks
by: Mei, Wenjie, et al.
Published: (2024)

Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)
by: Braniff, Austin, et al.
Published: (2025)

HyperController: A Hyperparameter Controller for Fast and Stable Training of Reinforcement Learning Neural Networks
by: Gornet, Jonathan, et al.
Published: (2025)

Linearization of ReLU Activation Function for Neural Network-Embedded Optimization: Optimal Day-Ahead Energy Scheduling
by: Zhao, Cunzhi, et al.
Published: (2023)

Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations
by: Liu, Jun
Published: (2026)

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial
by: Li, Haoyu, et al.
Published: (2026)

Learning Subsystem Dynamics in Nonlinear Systems via Port-Hamiltonian Neural Networks
by: van Otterdijk, G. J. E., et al.
Published: (2024)

System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models
by: Li, Xiao, et al.
Published: (2023)

Extracting Forward Invariant Sets from Neural Network-Based Control Barrier Functions
by: Vaisi, Goli, et al.
Published: (2025)