Jonathan Dong

According to our database, Jonathan Dong authored at least 17 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Comparison of Reservoir Computing topologies using the Recurrent Kernel approach.

Giuseppe Alessio D'Inverno, Jonathan Dong

Neurocomputing, 2025

2024

Quantitative Unmixing in Photoswitching Optoacoustic Tomography.

Yan Liu, Jonathan Chuah, Andre C. Stiel, Michael Unser, Jonathan Dong

Dataset, May, 2024

Extension of Recurrent Kernels to different Reservoir Computing topologies.

Giuseppe Alessio D'Inverno, Jonathan Dong

CoRR, 2024

Detection and Positive Reconstruction of Cognitive Distortion Sentences: Mandarin Dataset and Evaluation.

Shuya Lin, Yuxiong Wang, Jonathan Dong, Shiguang Ni

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial.

Jonathan Dong, Lorenzo Valzania, Antoine Maillard, Thanh-An Pham, Sylvain Gigan, Michael Unser

IEEE Signal Process. Mag., 2023

Mechanical Artifacts in Optical Projection Tomography: Classification and Automatic Calibration.

Yan Liu, Jonathan Dong, Thanh-An Pham, François Marelli, Michael Unser

CoRR, 2023

2022

Mechanical Artifacts in Optical Projection Tomography: Classification and Automatic Calibration.

Yan Liu, Jonathan Dong, Thanh-An Pham, François Marelli, Michael Unser

Dataset, November, 2022

Dataset provided with "Artifacts in Optical Projection Tomography Due to Refractive-Index Mismatch: Model and Correction".

Yan Liu, Jonathan Dong, Cédric Schmidt, Aleix Boquet-Pujadas, Jérôme Extermann, Michael Unser

Dataset, February, 2022

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors.

Pakshal Bohra, Thanh-An Pham, Jonathan Dong, Michael Unser

IEEE Trans. Computational Imaging, 2022

Asymptotic Stability in Reservoir Computing.

Jonathan Dong, Erik Börve, Mushegh Rafayelyan, Michael Unser

Proceedings of the International Joint Conference on Neural Networks, 2022

2020

Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction.

Mushegh Rafayelyan, Jonathan Dong, Yongqi Tan, Florent Krzakala, Sylvain Gigan

CoRR, 2020

Reservoir Computing meets Recurrent Kernels and Structured Transforms.

Jonathan Dong, Ruben Ohana, Mushegh Rafayelyan, Florent Krzakala

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units.

Ruben Ohana, Jonas Wacker, Jonathan Dong, Sébastien Marmin, Florent Krzakala, Maurizio Filippone, Laurent Daudet

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Optical Reservoir Computing using multiple light scattering for chaotic systems prediction.

Jonathan Dong, Mushegh Rafayelyan, Florent Krzakala, Sylvain Gigan

CoRR, 2019

Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media.

Jonathan Dong, Florent Krzakala, Sylvain Gigan

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Scaling Up Echo-State Networks With Multiple Light Scattering.

Jonathan Dong, Sylvain Gigan, Florent Krzakala, Gilles Wainrib

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

2015

Experimental robustness of Fourier Ptychography phase retrieval algorithms.

Li-Hao Yeh, Jonathan Dong, Jingshan Zhong, Lei Tian, Michael Chen, Gongguo Tang, Mahdi Soltanolkotabi, Laura Waller

CoRR, 2015