Yiming Meng

According to our database, Yiming Meng authored at least 17 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction.

Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou

CoRR, 2024

Compositionally Verifiable Vector Neural Lyapunov Functions for Stability Analysis of Interconnected Nonlinear Systems.

Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou

CoRR, 2024

Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification.

Yiming Meng, Ruikun Zhou, Amartya Mukherjee, Maxwell Fitzsimmons, Christopher Song, Jun Liu

CoRR, 2024

Physics-Informed Neural Networks for Stability Analysis and Control with Formal Guarantees.

Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou

Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control, 2024

TOOL LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction.

Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou

Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control, 2024

2023

Hopf Bifurcations of Moore-Greitzer PDE Model with Additive Noise.

Yiming Meng, Navaratnam Sri Namachchivaya, Nicolas Perkowski

J. Nonlinear Sci., October, 2023

Stochastic Control Barrier Functions with Bayesian Inference for Unknown Stochastic Differential Equations.

Chuanzheng Wang, Yiming Meng, Jun Liu, Stephen L. Smith

CoRR, 2023

Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification.

Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou

CoRR, 2023

Robustly Complete Finite-State Abstractions for Control Synthesis of Stochastic Systems.

Yiming Meng, Jun Liu

CoRR, 2023

Towards Learning and Verifying Maximal Neural Lyapunov Functions.

Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Smooth converse Lyapunov-barrier theorems for asymptotic stability with safety constraints and reach-avoid-stay specifications.

Yiming Meng, Yinan Li, Maxwell Fitzsimmons, Jun Liu

Autom., 2022

Robustly Complete Finite-State Abstractions for Verification of Stochastic Systems.

Yiming Meng, Jun Liu

Proceedings of the Formal Modeling and Analysis of Timed Systems, 2022

Data-Driven Learning of Safety-Critical Control with Stochastic Control Barrier Functions.

Chuanzheng Wang, Yiming Meng, Stephen L. Smith, Jun Liu

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Sufficient Conditions for Robust Probabilistic Reach-Avoid-Stay Specifications using Stochastic Lyapunov-Barrier Functions.

Yiming Meng, Jun Liu

Proceedings of the American Control Conference, 2022

2021

Learning Control Barrier Functions with High Relative Degree for Safety-Critical Control.

Chuanzheng Wang, Yiming Meng, Yinan Li, Stephen L. Smith, Jun Liu

Proceedings of the 2021 European Control Conference, 2021

Safety-Critical Control of Stochastic Systems using Stochastic Control Barrier Functions.

Chuanzheng Wang, Yiming Meng, Stephen L. Smith, Jun Liu

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Control of Nonlinear Systems with Reach-Avoid-Stay Specifications: A Lyapunov-Barrier Approach with an Application to the Moore-Greizer Model.

Yiming Meng, Yinan Li, Jun Liu

Proceedings of the 2021 American Control Conference, 2021