323 citations · 1.3k across the 22 of their papers we have counts for
22 papers
Optical Reservoir Computing with Structural Nonlinearity for Forecasting Chaotic Time Series
Leandro R. Venâncio, Jonathan Dong, Mickael Mounaix +1
Optical computing offers a promising route to high-speed, energy-efficient information processing. However, implementing nonlinear operations typically requires strong light-matter…
Single-pixel transmission matrix recovery via 2-photon fluorescence
Shupeng Zhao, Bernhard Rauer, Lorenzo Valzania +5
Imaging at depth in opaque materials has long been a challenge. Recently, wavefront shaping has enabled significant advance for deep imaging. Nevertheless, most non-invasive wavefr…
Asymptotic Stability in Reservoir Computing
Jonathan Dong, Erik Börve, Mushegh Rafayelyan +1
Reservoir Computing is a class of Recurrent Neural Networks with internal weights fixed at random. Stability relates to the sensitivity of the network state to perturbations. It is…
Physics-based neural network for non-invasive control of coherent light in scattering media
Alexandra d'Arco, Fei Xia, Antoine Boniface +2
Optical imaging through complex media, such as biological tissues or fog, is challenging due to light scattering. In the multiple scattering regime, wavefront shaping provides an e…
Phase Retrieval: From Computational Imaging to Machine Learning
Jonathan Dong, Lorenzo Valzania, Antoine Maillard +3
Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven…
Bayesian Inversion for Nonlinear Imaging Models using Deep Generative Priors
Pakshal Bohra, Thanh-an Pham, Jonathan Dong +1
Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse pr…