Convergence Speed
Cross-source consensus on Convergence Speed from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Benefits
Dosage & preparation
Highlighted claims
- ML-augmented reconstruction converges faster while reaching final Poisson NLL values comparable to the standard algorithm. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction
- Using iteration-to-epsilon, the ML method reduces wall-clock time by 2.1x to 2.3x. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction
- The ML insertion can briefly increase Poisson NLL before gradient-based updates restore data consistency. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction
- Early ML insertion at iteration 3 or 5 gives the lowest convergence iterations in the hyperparameter study. — Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction