22 citations · 23 across the 8 of their papers we have counts for
8 papers
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…
Learning partially observed systems with neural Hamiltonian ordinary differential equations
Sunniva Meltzer, Sølve Eidnes, Alexander Johannes Stasik
When learning dynamical systems from data, embedding physical structure can constrain the solution space and improve generalization, but many physics-informed models assume access…
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…
A Quantum Encoding of Traveling Salesperson Tours via Route Generation, Cost Phases, and a Reversible Valid-Permutation Oracle
Alexander Johannes Stasik, Franz Georg Fuchs
For a traveling salesperson problem (TSP) of cities, we present a compact quantum encoding based on a time-register representation of tours. A candidate route is represented as…
Unreliable Uncertainty Estimates with Monte Carlo Dropout
Aslak Djupskås, Alexander Johannes Stasik, Signe Riemer-Sørensen
Reliable uncertainty estimation is crucial for machine learning models, especially in safety-critical domains. While exact Bayesian inference offers a principled approach, it is of…
Quantum reservoir computing using the stabilizer formalism for encoding classical data
Franz G. Fuchs, Alexander J. Stasik, Stanley Miao +2
Utilizing a quantum system for reservoir computing has recently received a lot of attention. Key challenges are related to how on can optimally en- and decode classical information…
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…
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces
Sølve Eidnes, Alexander J. Stasik, Camilla Sterud +2
Hybrid machine learning based on Hamiltonian formulations has recently been successfully demonstrated for simple mechanical systems, both energy conserving and not energy conservin…