1 citations · 1 across the 4 of their papers we have counts for
4 papers
A Physics-Informed Neural Network with a Modified Lorentzian Activation for Nonlocal Gradient-Flow Equations in Dynamic Density Functional Theory
Dimitrios Gourzoulidis, Soumaya Elkantassi, Serafim Kalliadasis
We develop a physics-informed neural network (PINN) framework for nonlocal partial differential equations arising in dynamic density functional theory (DDFT). Such equations are ch…
Inference on the Miss Distance in a Conjunction
J. Russell Carpenter, Anthony C. Davison, Soumaya Elkantassi +1
Over the last quarter-century, spacecraft conjunction assessment has focused on a quantity associated by its advocates with collision probability. This quantity has a well-known di…
Statistical Inference on the Miss Distance Compared to Collision Probability for Conjunction Analysis
Soumaya Elkantassi, Valérie Chavez-Demoulin, Anthony C. Davison +2
Satellite conjunctions involving near misses of space objects are increasingly common, especially with the growth of satellite constellations and space debris. Accurate risk analys…
Space Oddity? A Statistical Formulation of Conjunction Assessment
Soumaya Elkantassi, Anthony Davison
Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision p…