activity
20232025
collaborators

7 papers

math.NA2025

Non-intrusive structural-preserving sequential data assimilation

Lizuo Liu, Tongtong Li, Anne Gelb

Data assimilation (DA) methods combine model predictions with observational data to improve state estimation in dynamical systems, inspiring their increasingly prominent role in ge…

math.NA2025

Structurally informed data assimilation in two dimensions

Tongtong Li, Anne Gelb, Yoonsang Lee

Accurate data assimilation (DA) for systems with piecewise-smooth or discontinuous state variables remains a significant challenge, as conventional covariance-based ensemble Kalman…

math.NA2025

The Bayesian SIAC filter

Jan Glaubitz, Tongtong Li, Jennifer Ryan +1

We propose the Bayesian Smoothness-Increasing Accuracy-Conserving (SIAC) filter---a hierarchical Bayesian generalization of the existing deterministic SIAC filter. The SIAC filter…

math.NA2024

Entropy stable conservative flux form neural networks

Lizuo Liu, Tongtong Li, Anne Gelb +1

We propose an entropy-stable conservative flux form neural network (CFN) that integrates classical numerical conservation laws into a data-driven framework using the entropy-stable…

math.NA2024

A Bayesian framework for spectral reprojection

Tongtong Li, Anne Gelb

Fourier partial sum approximations yield exponential accuracy for smooth and periodic functions, but produce the infamous Gibbs phenomenon for non-periodic ones. Spectral reproject…

math.AP2024

Very weak solutions of the Dirichlet problem for 2-Hessian equation

Tongtong Li, Guohuan Qiu

For any small, we construct infinitely many very weak solutions to the 2-Hessian equation with prescribed boundary value. The proof relies on the convex integration m…

math.NA2023

A Structurally Informed Data Assimilation Approach for Nonlinear Partial Differential Equations

Tongtong Li, Anne Gelb, Yoonsang Lee

Ensemble transform Kalman filtering (ETKF) data assimilation is often used to combine available observations with numerical simulations to obtain statistically accurate and reliabl…