Jason J. Bramburger

According to our database, Jason J. Bramburger authored at least 19 papers between 2019 and 2026.

Collaborative distances:

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

2026

Learning Graphons From Data: Random Walks, Transfer Operators, and Spectral Clustering.

Stefan Klus, Jason J. Bramburger

IEEE Trans. Signal Process., 2026

Localized Patterns.

Jason J. Bramburger, Dan J. Hill, David J. B. Lloyd

SIAM Rev., 2026

2025

Persistence of Steady States for Dynamical Systems on Large Networks.

Jason J. Bramburger, Matt Holzer, Jackson Williams

J. Nonlinear Sci., December, 2025

Real-time motion detection using dynamic mode decomposition.

Marco Mignacca, Simone Brugiapaglia, Jason J. Bramburger

EURASIP J. Image Video Process., December, 2025

Weighted Birkhoff Averages Accelerate Data-Driven Methods.

Maria Bou-Sakr-El-Tayar, Jason J. Bramburger, Matthew J. Colbrook

CoRR, November, 2025

Reconstruction of frequency-localized functions from pointwise samples via least squares and deep learning.

A. Martina Neuman, Andres Felipe Lerma Pineda, Jason J. Bramburger, Simone Brugiapaglia

CoRR, February, 2025

Data-Driven Stabilization of Unstable Periodic Orbits of the Three-Body Problem.

Owen M. Brook, Jason J. Bramburger, Davide Amato, Urban Fasel

IEEE Access, 2025

2024

Auxiliary Functions as Koopman Observables: Data-Driven Analysis of Dynamical Systems via Polynomial Optimization.

Jason J. Bramburger, Giovanni Fantuzzi

J. Nonlinear Sci., February, 2024

Synthesizing Control Laws from Data using Sum-of-Squares Optimization.

Jason J. Bramburger, Steven Dahdah, James Richard Forbes

Proceedings of the IEEE Conference on Control Technology and Applications, 2024

2023

Convex Relaxations of Integral Variational Problems: Pointwise Dual Relaxation and Sum-of-Squares Optimization.

Alexander Chernyavsky, Jason J. Bramburger, Giovanni Fantuzzi, David Goluskin

SIAM J. Optim., 2023

Transferability of Graph Neural Networks using Graphon and Sampling Theories.

A. Martina Neuman, Jason J. Bramburger

CoRR, 2023

Auxiliary Functions as Koopman Observables: Data-Driven Polynomial Optimization for Dynamical Systems.

Jason J. Bramburger, Giovanni Fantuzzi

CoRR, 2023

2022

The Experimental Multi-Arm Pendulum on a Cart: A Benchmark System for Chaos, Learning, and Control.

Kadierdan Kaheman, Urban Fasel, Jason J. Bramburger, Benjamin Strom, J. Nathan Kutz, Steven L. Brunton

CoRR, 2022

2021

Deep Learning of Conjugate Mappings.

Jason J. Bramburger, Steven L. Brunton, J. Nathan Kutz

CoRR, 2021

Exact minimum speed of traveling waves in a Keller-Segel model.

Jason J. Bramburger

Appl. Math. Lett., 2021

Data-Driven Stabilization of Periodic Orbits.

Jason J. Bramburger, J. Nathan Kutz, Steven L. Brunton

IEEE Access, 2021

2020

Spatially Localized Structures in Lattice Dynamical Systems.

Jason J. Bramburger, Björn Sandstede

J. Nonlinear Sci., 2020

Sparse Identification of Slow Timescale Dynamics.

Jason J. Bramburger, Daniel Dylewsky, J. Nathan Kutz

CoRR, 2020

2019

Localized Radial Roll Patterns in Higher Space Dimensions.

Jason J. Bramburger, Dylan J. Altschuler, Chloe I. Avery, Tharathep Sangsawang, Margaret Beck, Paul Carter, Björn Sandstede

SIAM J. Appl. Dyn. Syst., 2019