Search Results for author:
Found 5 papers, 1 papers with code
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging
The proposed method employs estimates of the posterior variance together with techniques from conformal prediction in order to obtain coverage guarantees for the error bounds, without making any assumption on the underlying data distribution.
Unsupervised energy disaggregation via convolutional sparse coding
In this work, a method for unsupervised energy disaggregation in private households equipped with smart meters is proposed.
Latent-space disentanglement with untrained generator networks for the isolation of different motion types in video data
Isolating different types of motion in video data is a highly relevant problem in video analysis.
Accelerometry-based classification of circulatory states during out-of-hospital cardiac arrest
Methods: We developed a machine learning algorithm to automatically predict the circulatory state during cardiopulmonary resuscitation from 4-second-long snippets of accelerometry and electrocardiogram (ECG) data from pauses of chest compressions of real-world defibrillator records.
A Note on the Regularity of Images Generated by Convolutional Neural Networks
The regularity of images generated by convolutional neural networks, such as the U-net, generative networks, or the deep image prior, is analyzed.
