182 citations · 196 across the 5 of their papers we have counts for
5 papers
Fast and Accurate Inverse Blood Flow Modeling from Minimal Cuff-Pressure Data via PINNs
Sokratis J. Anagnostopoulos, Georgios Rovas, Lydia Aslanidou +2
Accurate assessment of central hemodynamics is essential for diagnosis and risk stratification, yet it still relies largely on invasive measurements or on indirect reconstructions…
Real-Time Surrogate Modeling for Personalized Blood Flow Prediction and Hemodynamic Analysis
Sokratis J. Anagnostopoulos, George Rovas, Vasiliki Bikia +3
Cardiovascular modeling has rapidly advanced over the past few decades due to the rising needs for health tracking and early detection of cardiovascular diseases. While 1-D arteria…
Learning in PINNs: Phase transition, diffusion equilibrium, and generalization
Sokratis J. Anagnostopoulos, Juan Diego Toscano, Nikolaos Stergiopulos +1
We investigate the learning dynamics of fully-connected neural networks through the lens of the neural gradient signal-to-noise ratio (SNR), examining the behavior of first-order o…
Residual-based attention in physics-informed neural networks
Sokratis J. Anagnostopoulos, Juan Diego Toscano, Nikolaos Stergiopulos +1
Driven by the need for more efficient and seamless integration of physical models and data, physics-informed neural networks (PINNs) have seen a surge of interest in recent years.…
Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models
Sokratis Anagnostopoulos, Jens Bauer, Mariana C. A. Clare +1
Wind farm modelling has been an area of rapidly increasing interest with numerous analytical as well as computational-based approaches developed to extend the margins of wind farm…