Imagen de Portada

Mixed Monotonicity Reachability Analysis of Neural ODE: A Trade-Off Between Tightness and Efficiency

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Sayed, Abdelrahman Sayed, Meyer, Pierre-Jean, Ghazel, Mohamed
Formato:	Preprint
Publicado:	2025
Materias:	Systems and Control Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification
por: Sayed, Abdelrahman Sayed, et al.
Publicado: (2025)

HyperKKL: Enabling Non-Autonomous State Estimation through Dynamic Weight Conditioning
por: Shaaban, Yahia Salaheldin, et al.
Publicado: (2026)

$\texttt{immrax}$: A Parallelizable and Differentiable Toolbox for Interval Analysis and Mixed Monotone Reachability in JAX
por: Harapanahalli, Akash, et al.
Publicado: (2024)

HyperKKL: Learning KKL Observers for Non-Autonomous Nonlinear Systems via Hypernetwork-Based Input Conditioning
por: Shaaban, Yahia Salaheldin, et al.
Publicado: (2026)

Quadratic Characterizations for Reachability Analysis of Neural Networks
por: Khalife, Elias, et al.
Publicado: (2026)

Risk Assessment of an Autonomous Underwater Snake Robot in Confined Operations
por: Sayed, Abdelrahman Sayed
Publicado: (2025)

Efficient Reachability Analysis for Convolutional Neural Networks Using Hybrid Zonotopes
por: Zhang, Yuhao, et al.
Publicado: (2025)

Provable Bounds on the Hessian of Neural Networks: Derivative-Preserving Reachability Analysis
por: Sharifi, Sina, et al.
Publicado: (2024)

Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems
por: Harapanahalli, Akash, et al.
Publicado: (2023)

Lyapunov Neural ODE State-Feedback Control Policies
por: Ip, Joshua Hang Sai, et al.
Publicado: (2024)

High-Probability Convergence Guarantees of Decentralized SGD
por: Armacki, Aleksandar, et al.
Publicado: (2025)

Neural Approximators for Low-Thrust Trajectory Transfer Cost and Reachability
por: Zhang, Zhong, et al.
Publicado: (2025)

Diffusion Stochastic Learning Over Adaptive Competing Networks
por: Zhao, Yike, et al.
Publicado: (2025)

High-Probability Convergence in Decentralized Stochastic Optimization with Gradient Tracking
por: Armacki, Aleksandar, et al.
Publicado: (2026)

Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets
por: Solanki, Prashant, et al.
Publicado: (2025)

Data-Driven Reachability Analysis via Diffusion Models with PAC Guarantees
por: Huang, Yanliang, et al.
Publicado: (2026)

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

Causal Influence in Federated Edge Inference
por: Kayaalp, Mert, et al.
Publicado: (2024)

Convex Hulls of Reachable Sets
por: Lew, Thomas, et al.
Publicado: (2023)

Safe LLM-Controlled Robots with Formal Guarantees via Reachability Analysis
por: Hafez, Ahmad, et al.
Publicado: (2025)

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially Observable Environments
por: Zhaikhan, Ainur, et al.
Publicado: (2024)

Compressed Regression over Adaptive Networks
por: Carpentiero, Marco, et al.
Publicado: (2023)

Distributed Adaptive Learning Under Communication Constraints
por: Carpentiero, Marco, et al.
Publicado: (2021)

Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers
por: Shen, Keyi, et al.
Publicado: (2026)

Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis
por: Lin, Albert, et al.
Publicado: (2025)

Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey
por: Ganai, Milan, et al.
Publicado: (2024)

Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
por: Prajapat, Manish, et al.
Publicado: (2025)

Symplectic Inductive Bias for Data-Driven Target Reachability in Hamiltonian Systems
por: Ouyang, Zhuo, et al.
Publicado: (2026)

Tight Long-Term Tail Decay of (Clipped) SGD in Non-Convex Optimization
por: Armacki, Aleksandar, et al.
Publicado: (2026)

Learning to Control Unknown Strongly Monotone Games
por: Chandak, Siddharth, et al.
Publicado: (2024)

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
por: Zhang, Qixin, et al.
Publicado: (2025)

Data-driven Reachable Set Estimation with Tunable Adversarial and Wasserstein Distributional Guarantees
por: Pantazis, Georgios, et al.
Publicado: (2026)

Analysis of Off-Policy Multi-Step TD-Learning with Linear Function Approximation
por: Lee, Donghwan
Publicado: (2024)

Verification of Neural Reachable Tubes via Scenario Optimization and Conformal Prediction
por: Lin, Albert, et al.
Publicado: (2023)

The Reachability Problem for Neural-Network Control Systems
por: Schilling, Christian, et al.
Publicado: (2024)

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

Online Adaptation for Flying Quadrotors in Tight Formations
por: Hsieh, Pei-An, et al.
Publicado: (2025)

Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
por: Zhong, Yaofeng Desmond, et al.
Publicado: (2019)

Scalable Data-Driven Reachability Analysis and Control via Koopman Operators with Conformal Coverage Guarantees
por: Nath, Devesh, et al.
Publicado: (2026)

A Hybrid Strategy for Probabilistic Forecasting and Trading of Aggregated Wind-Solar Power: Design and Analysis in HEFTCom2024
por: Pu, Chuanqing, et al.
Publicado: (2025)