3 papers
stat.ML2026
Auto-differentiable data assimilation: Co-learning of states, dynamics, and filtering algorithms
Melissa Adrian, Daniel Sanz-Alonso, Rebecca Willett
Data assimilation algorithms estimate the state of a dynamical system from partial observations, where the successful performance of these algorithms hinges on costly parameter tun…
stat.ML2025
Stabilizing black-box model selection with the inflated argmax
Melissa Adrian, Jake A. Soloff, Rebecca Willett
Model selection is the process of choosing from a class of candidate models given data. For instance, methods such as the LASSO and sparse identification of nonlinear dynamics (SIN…
eess.SP2025
Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet
Melissa Adrian, Daniel Sanz-Alonso, Rebecca Willett
Modern data-driven surrogate models for weather forecasting provide accurate short-term predictions but inaccurate and nonphysical long-term forecasts. This paper investigates onli…