11. A. Balakrishna, E. Carlson, P. C. Jayanti Data assimilation and local-in-time global control of inviscid systems using partially resolved measurements, Phys. D: Nonlinear Phenom., 483, 134929, (2025).
10. J. Newey, J. Whitehead, E. Carlson Model discovery using sensitivity equations, J. of Comp. Phys., 537, 114121, (2025).
9. E. Carlson, A. Farhat, V. R. Martinez, C. Victor On the Infinite-Nudging Limit of the Nudging Filter for Continuous Data Assimilation (submitted)
8. E. Carlson, A. Farhat, V. R. Martinez, C. Victor Determining Modes, Synchronization, and Intertwinement (submitted)
7. F. Bleitner, E. Carlson, C. Nobili Large time behaviour of the 2D thermally non-diffusive Boussinesq equations with Navier-slip boundary conditions Z. Angew. Math. Phys. 76, 58 (2025).
6. E. Carlson, A. Larios, E.S. Titi. Super-exponential convergence rate of a nonlinear continuous data assimilation algorithm: The 2D Navier-Stokes equations paradigm. J. Nonlinear Sci. 34, Article 37, (2024).
5. E. Carlson, J. Hudson, A. Larios, V. R. Martinez, E. Ng, J. P. Whitehead. Dynamically learning the parameters of a chaotic system using partial observations DCDS, 32, no. 8 (2022).
4. E. Carlson, L. Van Roekel, H. Godinez, M. Petersen, A. Larios. CDA Algorithm Implemented in MPAS-O To Improve Eddy Effects in a Mesoscale Simulation (submitted).
3. E. Carlson, A. Larios. Sensitivity Analysis for the 2D Navier-Stokes Equations with Applications to Continuous Data Assimilation J. Nonlinear Sci., 31, no. 84, (2021).
2. E. Carlson, J. Hudson, A. Larios. Parameter Recovery for the 2D Navier-Stokes Equations Via Continuous Data Assimilation. SIAM J. Sci. Comput, 42, no. 1, (2020), pp. 250–270.
(please email me for a copy)
1. E. Carlson, E. Sullivan. Fish Mixing . UMAP, Vol. 37, No. 4, 2016. (also featured as a classroom resource in Tactile Learning Activities in Mathematics: A Recipe Book for the Undergraduate Classroom. September 2018.)