Michael Wells

According to our database, Michael Wells authored at least 7 papers between 2007 and 2025.

Collaborative distances:

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

2025

The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations.

Michael Wells, Kamel Lahouel, Bruno Jedynak

CoRR, May, 2025

MOCK: an Algorithm for Learning Nonparametric Differential Equations via Multivariate Occupation Kernel Functions.

Victor Rielly, Kamel Lahouel, Ethan Lew, Nicholas Fisher, Vicky Haney, Michael Wells, Bruno M. Jedynak

Trans. Mach. Learn. Res., 2025

2024

Learning nonparametric ordinary differential equations from noisy data.

Kamel Lahouel, Michael Wells, Victor Rielly, Ethan Lew, David Lovitz, Bruno M. Jedynak

J. Comput. Phys., 2024

The Stochastic Occupation Kernel Method for System Identification.

Michael Wells, Kamel Lahouel, Bruno Jedynak

CoRR, 2024

2023

Learning High-Dimensional Nonparametric Differential Equations via Multivariate Occupation Kernel Functions.

Victor Rielly, Kamel Lahouel, Ethan Lew, Michael Wells, Vicky Haney, Bruno Jedynak

CoRR, 2023

2022

Learning Nonparametric Ordinary differential Equations: Application to Sparse and Noisy Data.

Kamel Lahouel, Michael Wells, David Lovitz, Victor Rielly, Ethan Lew, Bruno Jedynak

CoRR, 2022

2007

Experiences in Deploying Model-Driven Engineering.

Thomas Weigert, Frank Weil, Kevin Marth, Paul Baker, Clive Jervis, Paul H. Dietz, Yexuan Gui, Aswin van den Berg, Kim Fleer, David Nelson, Michael Wells, Brian E. Mastenbrook

Proceedings of the SDL 2007: Design for Dependable Systems, 2007