29 citations · 40 across the 12 of their papers we have counts for
4 papers · 1 filter
Constrained Sensing and Reliable State Estimation with Shallow Recurrent Decoders on a TRIGA Mark II Reactor
Stefano Riva, Carolina Introini, Josè Nathan Kutz +1
Shallow Recurrent Decoder networks are a novel data-driven methodology able to provide accurate state estimation in engineering systems, such as nuclear reactors. This deep learnin…
A Comparison of Parametric Dynamic Mode Decomposition Algorithms for Thermal-Hydraulics Applications
Stefano Riva, Andrea Missaglia, Carolina Introini +2
In recent years, algorithms aiming at learning models from available data have become quite popular due to two factors: 1) the significant developments in Artificial Intelligence t…
From Models To Experiments: Shallow Recurrent Decoder Networks on the DYNASTY Experimental Facility
Stefano Riva, Andrea Missaglia, Carolina Introini +2
The Shallow Recurrent Decoder networks are a novel paradigm recently introduced for state estimation, combining sparse observations with high-dimensional model data. This architect…
Towards Efficient Parametric State Estimation in Circulating Fuel Reactors with Shallow Recurrent Decoder Networks
Stefano Riva, Carolina Introini, J. Nathan Kutz +1
The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering systems; nuclear reactors represent p…