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Integrated Modeling and Reconstruction with Sparsity Constraints for fDOT

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Integrated Modeling and Reconstruction with Sparsity Constraints for fDOT

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Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Aggregating Spatial and Photometric Context for Photometric Stereo

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Random matrix methods for high-dimensional machine learning models

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

Bayes-optimal Learning of Deep Random Networks of Extensive-width

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Aggregating Spatial and Photometric Context for Photometric Stereo

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Random matrix methods for high-dimensional machine learning models

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

Bayes-optimal Learning of Deep Random Networks of Extensive-width

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods