| Convolutional Dictionary Learning by End-To-End Training of Iterative Neural Networks. | 0 | 0.34 | 2022 |
| Discretization of Learned NETT Regularization for Solving Inverse Problems. | 0 | 0.34 | 2021 |
| Combining Reconstruction and Edge Detection in Computed Tomography. | 0 | 0.34 | 2021 |
| Multiscale Factorization Of The Wave Equation With Application To Compressed Sensing Photoacoustic Tomography | 0 | 0.34 | 2021 |
| Recovering The Initial Data Of The Wave Equation From Neumann Traces | 0 | 0.34 | 2021 |
| Sparse Anett For Solving Inverse Problems With Deep Learning | 0 | 0.34 | 2020 |
| Big in Japan: Regularizing Networks for Solving Inverse Problems | 0 | 0.34 | 2020 |
| A machine learning framework for customer purchase prediction in the non-contractual setting | 0 | 0.34 | 2020 |
| Reconstruction Algorithms for Photoacoustic Tomography in Heterogeneous Damping Media. | 0 | 0.34 | 2019 |
| Random 2.5D U-net for Fully 3D Segmentation. | 0 | 0.34 | 2019 |
| Analysis of the Block Coordinate Descent Method for Linear Ill-Posed Problems | 0 | 0.34 | 2019 |
| Operator Learning Approach for the Limited View Problem in Photoacoustic Tomography | 0 | 0.34 | 2019 |
| Image Based Fashion Product Recommendation with Deep Learning. | 0 | 0.34 | 2018 |
| Stochastic Proximal Gradient Algorithms for Multi-Source Quantitative Photoacoustic Tomography. | 0 | 0.34 | 2018 |
| Analysis of the Linearized Problem of Quantitative Photoacoustic Tomography. | 1 | 0.36 | 2018 |
| A U-Nets Cascade for Sparse View Computed Tomography. | 0 | 0.34 | 2018 |
| A Framework for Compressive Time-of-Flight 3D Sensing. | 0 | 0.34 | 2017 |
| Analytic Inversion of a Conical Radon Transform Arising in Application of Compton Cameras on the Cylinder. | 1 | 0.36 | 2017 |
| Inversion of the Attenuated V-Line Transform With Vertices on the Circle. | 0 | 0.34 | 2017 |
| Analysis of Iterative Methods in Photoacoustic Tomography with Variable Sound Speed. | 8 | 0.70 | 2017 |
| The Radon Transform over Cones with Vertices on the Sphere and Orthogonal Axes. | 2 | 0.42 | 2017 |
| Deep Learning For Photoacoustic Tomography From Sparse Data | 16 | 0.92 | 2017 |
| Sampling Conditions for the Circular Radon Transform. | 4 | 0.56 | 2016 |
| Universal Inversion Formulas for Recovering a Function from Spherical Means. | 11 | 0.73 | 2014 |
| Inversion of circular means and the wave equation on convex planar domains | 7 | 0.87 | 2013 |
| Stable Signal Reconstruction via 1 -Minimization in Redundant, Non-Tight Frames. | 0 | 0.34 | 2013 |
| A Mollification Approach for Inverting the Spherical Mean Radon Transform. | 5 | 0.57 | 2011 |
| Inversion Formulas for a Cylindrical Radon Transform | 2 | 0.43 | 2011 |
| The residual method for regularizing ill-posed problems. | 6 | 0.62 | 2011 |
| Inversion of Spherical Means and the Wave Equation in Even Dimensions | 11 | 1.53 | 2007 |
