1 citations · 1 across the 5 of their papers we have counts for
5 papers
ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability
Anthony Frion, Vien Minh Nguyen-Thanh, Ali Can Bekar +3
Data assimilation (DA) is an essential tool for prediction and understanding in the geosciences. DA combines simulation programs representing scientific knowledge with observations…
Uncertainty-aware data assimilation through variational inference
Anthony Frion, David S Greenberg
Data assimilation, consisting in the combination of a dynamical model with a set of noisy and incomplete observations in order to infer the state of a system over time, involves un…
Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates
Yunfei Huang, David S. Greenberg
Neural PDE surrogates can improve the cost-accuracy tradeoff of classical solvers, but often generalize poorly to new initial conditions and accumulate errors over time. Physical a…
sbi reloaded: a toolkit for simulation-based inference workflows
Jan Boelts, Michael Deistler, Manuel Gloeckler +30
Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a…
Combined Optimization of Dynamics and Assimilation with End-to-End Learning on Sparse Observations
Vadim Zinchenko, David S. Greenberg
Fitting nonlinear dynamical models to sparse and noisy observations is fundamentally challenging. Identifying dynamics requires data assimilation (DA) to estimate system states, bu…