activity
20182026
most citedA Levenberg-Marquardt algorithm for sparse identification of dynamical systems

25 citations · 56 across the 10 of their papers we have counts for

collaborators

12 papers

cs.LG2026

Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations

Berk Hadzhamolla, Alexander Johannes Stasik, Signe Riemer-Sørensen

Accurate modeling and forecasting of power transformer thermal behavior are critical for reliability, asset lifetime, and optimized power system operation. Numerical approaches suc…

cs.LG2026

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

Peter Collett, Alexander Johannes Stasik, Simone Casolo +1

Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertainty. While traditional Bayesi…

stat.AP2024★ 4 cited

Analysis of Full-scale Riser Responses in Field Conditions Based on Gaussian Mixture Model

Jie Wu, Sølve Eidnes, Jingzhe Jin +5

Offshore slender marine structures experience complex and combined load conditions from waves, current and vessel motions that may result in both wave frequency and vortex shedding…

eess.SY2024

Testing Topological Data Analysis for Condition Monitoring of Wind Turbines

Simone Casolo, Alexander Stasik, Zhenyou Zhang +1

We present an investigation of how topological data analysis (TDA) can be applied to condition-based monitoring (CBM) of wind turbines for energy generation. TDA is a branch of dat…

stat.ML2024

Recency-Weighted Temporally-Segmented Ensemble for Time-Series Modeling

Pål V. Johnsen, Eivind Bøhn, Sølve Eidnes +2

Time-series modeling in process industries faces the challenge of dealing with complex, multi-faceted, and evolving data characteristics. Conventional single model approaches often…

eess.SY2023

Pseudo-Hamiltonian system identification

Sigurd Holmsen, Sølve Eidnes, Signe Riemer-Sørensen

Identifying the underlying dynamics of physical systems can be challenging when only provided with observational data. In this work, we consider systems that can be modelled as fir…