52 citations · 71 across the 4 of their papers we have counts for
4 papers
Training Deep Physics-Informed Kolmogorov-Arnold Networks
Spyros Rigas, Fotios Anagnostopoulos, Michalis Papachristou +1
Since their introduction, Kolmogorov-Arnold Networks (KANs) have been successfully applied across several domains, with physics-informed machine learning (PIML) emerging as one of…
Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networks
Spyros Rigas, Michalis Papachristou, Ioannis Sotiropoulos +1
Rolling element bearings are critical components of rotating machinery, with their performance directly influencing the efficiency and reliability of industrial systems. At the sam…
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold Networks
Spyros Rigas, Michalis Papachristou, Theofilos Papadopoulos +2
Physics-Informed Neural Networks (PINNs) have emerged as a robust framework for solving Partial Differential Equations (PDEs) by approximating their solutions via neural networks a…
CO kinematics unveil outflows plausibly driven by a young jet in the Gigahertz Peaked Radio Core of NGC6328
Michalis Papachristou, Kalliopi Maria Dasyra, Juan Antonio Fernández-Ontiveros +3
We report the detection of outflowing molecular gas in the center of the nearby (z=0.014) massive radio galaxy NGC6328. The radio core of the galaxy, PKS B1718-649, is identified a…