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11/28/2022
Continuous diffusion for categorical data
Diffusion models have quickly become the go-to paradigm for generative m...
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06/26/2021
Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs
Cryo-electron microscopy (cryo-EM) has revolutionized experimental prote...
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07/29/2020
On the unreasonable effectiveness of CNNs
Deep learning methods using convolutional neural networks (CNN) have bee...
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01/24/2020
Kernel of CycleGAN as a Principle homogeneous space
Unpaired image-to-image translation has attracted significant interest d...
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08/19/2019
A unified representation network for segmentation with missing modalities
Over the last few years machine learning has demonstrated groundbreaking...
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08/01/2019
Multi-Scale Learned Iterative Reconstruction
Model-based learned iterative reconstruction methods have recently been ...
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11/14/2018
Deep Bayesian Inversion
Characterizing statistical properties of solutions of inverse problems i...
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08/27/2018
Task adapted reconstruction for inverse problems
The paper considers the problem of performing a task defined on a model ...
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08/14/2018
Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction
Digital breast tomosynthesis is rapidly replacing digital mammography as...
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06/18/2018
Banach Wasserstein GAN
Wasserstein Generative Adversarial Networks (WGANs) can be used to gener...
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01/17/2018
A modified fuzzy C means algorithm for shading correction in craniofacial CBCT images
CBCT images suffer from acute shading artifacts primarily due to scatter...
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10/30/2017
Learning to solve inverse problems using Wasserstein loss
We propose using the Wasserstein loss for training in inverse problems. ...
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07/20/2017
Learned Primal-dual Reconstruction
We propose the Learned Primal-Dual algorithm for tomographic reconstruct...
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04/13/2017