1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ML2023
On the Integration of Physics-Based Machine Learning with Hierarchical Bayesian Modeling Techniques
Omid Sedehi, Antonina M. Kosikova, Costas Papadimitriou +1
Machine Learning (ML) has widely been used for modeling and predicting physical systems. These techniques offer high expressive power and good generalizability for interpolation wi…
stat.AP2022★ 1 cited
Input-State-Parameter-Noise Identification and Virtual Sensing in Dynamical Systems: A Bayesian Expectation-Maximization (BEM) Perspective
Daniz Teymouri, Omid Sedehi, Lambros S. Katafygiotis +1
Structural identification and damage detection can be generalized as the simultaneous estimation of input forces, physical parameters, and dynamical states. Although Kalman-type fi…