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2020 – today
- 2024
[j1]Kamel Lahouel, Michael Wells, Victor Rielly, Ethan Lew
, David Lovitz, Bruno M. Jedynak:
Learning nonparametric ordinary differential equations from noisy data. J. Comput. Phys. 507: 112971 (2024)- [c3]Stanley Bak, Sergiy Bogomolov, Abdelrahman Hekal, Niklas Kochdumper, Ethan Lew, Andrew Mata, Amir Rahmati:
Falsification using Reachability of Surrogate Koopman Models. HSCC 2024: 27:1-27:13 - 2023
- [c2]Ethan Lew, Abdelrahman Hekal, Kostiantyn Potomkin, Niklas Kochdumper, Brandon Hencey, Stanley Bak, Sergiy Bogomolov:
AutoKoopman: A Toolbox for Automated System Identification via Koopman Operator Linearization. ATVA 2023: 237-250 - [i3]Victor Rielly, Kamel Lahouel, Ethan Lew, Michael Wells, Vicky Haney, Bruno Jedynak:
Learning High-Dimensional Nonparametric Differential Equations via Multivariate Occupation Kernel Functions. CoRR abs/2306.10189 (2023) - [i2]John M. Abowd, Tamara Adams, Robert Ashmead, David Darais, Sourya Dey, Simson L. Garfinkel, Nathan Goldschlag, Daniel Kifer, Philip Leclerc, Ethan Lew, Scott Moore, Rolando A. Rodríguez, Ramy N. Tadros, Lars Vilhuber:
The 2010 Census Confidentiality Protections Failed, Here's How and Why. CoRR abs/2312.11283 (2023) - 2022
- [c1]Stanley Bak, Sergiy Bogomolov, Brandon Hencey, Niklas Kochdumper, Ethan Lew, Kostiantyn Potomkin:
Reachability of Koopman Linearized Systems Using Random Fourier Feature Observables and Polynomial Zonotope Refinement. CAV (1) 2022: 490-510 - [i1]Kamel Lahouel, Michael Wells, David Lovitz, Victor Rielly, Ethan Lew, Bruno Jedynak:
Learning Nonparametric Ordinary differential Equations: Application to Sparse and Noisy Data. CoRR abs/2206.15215 (2022)
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