1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
RTS Smoother-Guided Learning of Physics-Based Neural Differential Models
Ahmet Demirkaya, Georgios Stratis, Tales Imbiriba +2
Ordinary differential equations (ODEs) are widely used to model dynamical systems in physics, biology, neuroscience, and physiology, but in many applications some equations of the…
cs.LG2024★ 1 cited
Learning Physics Informed Neural ODEs With Partial Measurements
Paul Ghanem, Ahmet Demirkaya, Tales Imbiriba +3
Learning dynamics governing physical and spatiotemporal processes is a challenging problem, especially in scenarios where states are partially measured. In this work, we tackle the…