3 papers
physics.optics2026
Controlling the Flow of Information in Optical Metrology
Maximilian Weimar, Huanli Zhou, Luca Neubacher +5
Optical metrology has progressed beyond the Abbe-Rayleigh limit, unlocking (sub)atomic precision by leveraging nonlinear phenomena, statistical accumulation, and AI estimators trai…
cs.LG2025
Fisher information flow in artificial neural networks
Maximilian Weimar, Lukas M. Rachbauer, Ilya Starshynov +4
The estimation of continuous parameters from measured data plays a central role in many fields of physics. A key tool in understanding and improving such estimation processes is th…
physics.optics2025
Model-free estimation of the Cramér-Rao bound for deep-learning microscopy in complex media
Ilya Starshynov, Maximilian Weimar, Lukas M. Rachbauer +4
Artificial neural networks have become important tools to harness the complexity of disordered or random photonic systems. Recent applications include the recovery of information f…