1 citations · 1 across the 3 of their papers we have counts for
3 papers
Graph neural networks uncover structure and functions underlying the activity of simulated neural assemblies
Cédric Allier, Larissa Heinrich, Magdalena Schneider +1
Graph neural networks trained to predict observable dynamics can be used to decompose the temporal activity of complex heterogeneous systems into simple, interpretable representati…
DeepPD: Joint Phase and Object Estimation from Phase Diversity with Neural Calibration of a Deformable Mirror
Magdalena C. Schneider, Courtney Johnson, Cedric Allier +6
Sample-induced aberrations and optical imperfections limit the resolution of fluorescence microscopy. Phase diversity is a powerful technique that leverages complementary phase inf…
Decomposing heterogeneous dynamical systems with graph neural networks
Cédric Allier, Magdalena C. Schneider, Michael Innerberger +3
Natural physical, chemical, and biological dynamical systems are often complex, with heterogeneous components interacting in diverse ways. We show how simple graph neural networks…