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Found 9 papers, 7 papers with code
Joint Cryo-ET Alignment and Reconstruction with Neural Deformation Fields
We show that our approach enables the recovery of high-frequency details that are destroyed without accounting for deformations.
Differentiable Uncalibrated Imaging
We propose a differentiable imaging framework to address uncertainty in measurement coordinates such as sensor locations and projection angles.
Contour-guided Image Completion with Perceptual Grouping
Humans are excellent at perceiving illusory outlines.
Total Least Squares Phase Retrieval
We address the phase retrieval problem with errors in the sensing vectors.
Improving the affordability of robustness training for DNNs
Projected Gradient Descent (PGD) based adversarial training has become one of the most prominent methods for building robust deep neural network models.
Fast Optical System Identification by Numerical Interferometry
Our method simplifies the calibration of optical transmission matrices from a quadratic to a linear inverse problem by first recovering the phase of the measurements.
Don't take it lightly: Phasing optical random projections with unknown operators
A signal of interest $\mathbf{\xi} \in \mathbb{R}^N$ is mixed by a random scattering medium to compute the projection $\mathbf{y} = \mathbf{A} \mathbf{\xi}$, with $\mathbf{A} \in \mathbb{C}^{M \times N}$ being a realization of a standard complex Gaussian iid random matrix.
Solving Complex Quadratic Systems with Full-Rank Random Matrices
We tackle the problem of recovering a complex signal $\boldsymbol x\in\mathbb{C}^n$ from quadratic measurements of the form $y_i=\boldsymbol x^*\boldsymbol A_i\boldsymbol x$, where $\boldsymbol A_i$ is a full-rank, complex random measurement matrix whose entries are generated from a rotation-invariant sub-Gaussian distribution.
Information Theory Information Theory
Random mesh projectors for inverse problems
We show that in this case the common approach to directly learn the mapping from the measured data to the reconstruction becomes unstable.
