most citedData-efficient Kernel Methods for Learning Hamiltonian Systems

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

math.NA2025★ 2 cited

Data-efficient Kernel Methods for Learning Hamiltonian Systems

Yasamin Jalalian, Mostafa Samir, Boumediene Hamzi +2

Hamiltonian dynamics describe a wide range of physical systems. As such, data-driven simulations of Hamiltonian systems are important for many scientific and engineering problems.…

stat.ME2021

Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball

Hamed Hamze Bajgiran, Pau Batlle Franch, Houman Owhadi +5

There are essentially three kinds of approaches to Uncertainty Quantification (UQ): (A) robust optimization, (B) Bayesian, (C) decision theory. Although (A) is robust, it is unfavo…