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ORCIDMaxwell Fitzsimmons
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2020 – today
- 2024
[j7]Maxwell Fitzsimmons
, Jun Liu:
A Neural Network Approach to Finding Global Lyapunov Functions for Homogeneous Vector Fields. IEEE Control. Syst. Lett. 8: 670-675 (2024)- [j6]Ruikun Zhou, Maxwell Fitzsimmons, Yiming Meng, Jun Liu:
Physics-Informed Extreme Learning Machine Lyapunov Functions. IEEE Control. Syst. Lett. 8: 1763-1768 (2024) - [c5]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
Compositionally Verifiable Vector Neural Lyapunov Functions for Stability Analysis of Interconnected Nonlinear Systems. ACC 2024: 4789-4794 - [c4]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
TOOL LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction. HSCC 2024: 25:1-25:8 - [c3]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
Physics-Informed Neural Networks for Stability Analysis and Control with Formal Guarantees. HSCC 2024: 32:1-32:2 - [c2]Yiming Meng, Ruikun Zhou, Amartya Mukherjee, Maxwell Fitzsimmons, Christopher Song, Jun Liu:
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification. ICML 2024 - [i7]Yiming Meng, Ruikun Zhou, Amartya Mukherjee, Maxwell Fitzsimmons, Christopher Song, Jun Liu:
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification. CoRR abs/2402.10119 (2024) - [i6]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
Compositionally Verifiable Vector Neural Lyapunov Functions for Stability Analysis of Interconnected Nonlinear Systems. CoRR abs/2403.10007 (2024) - [i5]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction. CoRR abs/2403.10013 (2024) - [i4]Jun Liu, Maxwell Fitzsimmons, Ruikun Zhou, Yiming Meng:
Formally Verified Physics-Informed Neural Control Lyapunov Functions. CoRR abs/2409.20528 (2024) - 2023
- [c1]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
Towards Learning and Verifying Maximal Neural Lyapunov Functions. CDC 2023: 8012-8019 - [i3]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
Towards Learning and Verifying Maximal Neural Lyapunov Functions. CoRR abs/2304.07215 (2023) - [i2]Jun Liu, Yiming Meng, Maxwell Fitzsimmons, Ruikun Zhou:
Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification. CoRR abs/2312.09131 (2023) - 2022
- [j5]Maxwell Fitzsimmons, Jun Liu:
A note on the equivalence of a strongly convex function and its induced contractive differential equation. Autom. 142: 110349 (2022) - [j4]Yiming Meng, Yinan Li, Maxwell Fitzsimmons, Jun Liu:
Smooth converse Lyapunov-barrier theorems for asymptotic stability with safety constraints and reach-avoid-stay specifications. Autom. 144: 110478 (2022) - 2020
- [j3]Maxwell Fitzsimmons, Herb Kunze:
Small and minimal attractors of an IFS. Commun. Nonlinear Sci. Numer. Simul. 85: 105227 (2020) - [j2]Maxwell Fitzsimmons, Herb Kunze:
Necessary/Sufficient Conditions for the Chaos Game to Render Quasi Attractors. Commun. Nonlinear Sci. Numer. Simul. 91: 105427 (2020) - [i1]Jun Liu, Yiming Meng, Yinan Li, Maxwell Fitzsimmons:
Smooth Converse Lyapunov-Barrier Theorems for Asymptotic Stability with Safety Constraints and Reach-Avoid-Stay Specifications. CoRR abs/2009.04432 (2020)
2010 – 2019
- 2019
- [j1]Maxwell Fitzsimmons, Herb Kunze:
Combining Hopfield neural networks, with applications to grid-based mathematics puzzles. Neural Networks 118: 81-89 (2019)
Coauthor Index
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