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04/24/2023
Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior
Variational auto-encoders (VAEs) are one of the most popular approaches ...
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04/17/2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
Bayesian methods for solving inverse problems are a powerful alternative...
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02/24/2023
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI
4D flow MRI is a non-invasive imaging method that can measure blood flow...
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11/13/2022
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
Shadows in videos are difficult to detect because of the large shadow de...
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09/16/2022
Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels
We propose WS-DINO as a novel framework to use weak label information in...
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09/05/2022
Imaging with Equivariant Deep Learning
From early image processing to modern computational imaging, successful ...
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10/07/2021
StyleGAN-induced data-driven regularization for inverse problems
Recent advances in generative adversarial networks (GANs) have opened up...
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05/10/2021
An end-to-end Optical Character Recognition approach for ultra-low-resolution printed text images
Some historical and more recent printed documents have been scanned or s...
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02/08/2021
A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation
Automatic segmentation methods are an important advancement in medical i...
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05/11/2020
iUNets: Fully invertible U-Nets with Learnable Up- and Downsampling
U-Nets have been established as a standard neural network design archite...
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04/11/2019
