3 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…
cs.LG2025
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…