11 citations · 11 across the 2 of their papers we have counts for
4 papers
A Generative Adversarial Approach To ECG Synthesis And Denoising
Karol Antczak
Generative Adversarial Networks (GAN) are known to produce synthetic data that are difficult to discern from real ones by humans. In this paper we present an approach to use GAN to…
Representation Learning for Medical Data
Karol Antczak
We propose a representation learning framework for medical diagnosis domain. It is based on heterogeneous network-based model of diagnostic data as well as modified metapath2vec al…
On Regularization Properties of Artificial Datasets for Deep Learning
Karol Antczak
The paper discusses regularization properties of artificial data for deep learning. Artificial datasets allow to train neural networks in the case of a real data shortage. It is de…
Deep Recurrent Neural Networks for ECG Signal Denoising
Karol Antczak
Electrocardiographic signal is a subject to multiple noises, caused by various factors. It is therefore a standard practice to denoise such signal before further analysis. With adv…