research
∙
03/15/2023
Learning to Reconstruct Signals From Binary Measurements
Recent advances in unsupervised learning have highlighted the possibilit...
share
research
∙
09/05/2022
Imaging with Equivariant Deep Learning
From early image processing to modern computational imaging, successful ...
research
∙
03/23/2022
Sampling Theorems for Unsupervised Learning in Linear Inverse Problems
Solving a linear inverse problem requires knowledge about the underlying...
research
∙
03/02/2022
Sketched RT3D: How to reconstruct billions of photons per second
Single-photon light detection and ranging (lidar) captures depth and int...
research
∙
01/28/2022
Sampling Theorems for Learning from Incomplete Measurements
In many real-world settings, only incomplete measurement data are availa...
research
∙
11/25/2021
Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements
Deep networks provide state-of-the-art performance in multiple imaging i...
research
∙
03/26/2021
Equivariant Imaging: Learning Beyond the Range Space
In various imaging problems, we only have access to compressed measureme...
research
∙
06/03/2020
CNN Denoisers As Non-Local Filters: The Neural Tangent Denoiser
Convolutional Neural Networks (CNNs) are now a well-established tool for...
research
∙
04/20/2020
Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences
In this paper, we present a new algorithm for fast, online 3D reconstruc...
research
∙
02/17/2020