Deep Generative Models for Physiological Signals: A Systematic Literature Review
In this paper, we present a systematic literature review on deep generative models for
physiological signals, particularly electrocardiogram, electroencephalogram …
physiological signals, particularly electrocardiogram, electroencephalogram …
Deep visual analytics (dva): applications, challenges and future directions
Visual interactive system (VIS) has been received significant attention for solving various
complex problems. However, designing and implementing a novel VIS with the large scale …
complex problems. However, designing and implementing a novel VIS with the large scale …
Lightweight transfer nets and adversarial data augmentation for photovoltaic series arc fault detection with limited fault data
Incidents of DC series arc faults in Photovoltaic (PV) systems are becoming more common,
posing significant threat to properties and human safety. Machine Learning (ML) based …
posing significant threat to properties and human safety. Machine Learning (ML) based …
An imbalanced data augmentation and assessment method for industrial process fault classification with application in air compressors
Y Shi, J Li, H Li, B Yang - IEEE Transactions on Instrumentation …, 2023 - ieeexplore.ieee.org
Imbalanced data samples can adversely affect the performance of industrial process fault
diagnosis models. Recently, it has become a valued challenge to expand data samples and …
diagnosis models. Recently, it has become a valued challenge to expand data samples and …
Evaluation of generative adversarial networks for time series data
H Arnout, J Bronner, T Runkler - 2021 International Joint …, 2021 - ieeexplore.ieee.org
In the last few years, several works have been proposed on Generative Adversarial
Networks (GAN). At the same time, there is a lack of investigation on their evaluation and the …
Networks (GAN). At the same time, there is a lack of investigation on their evaluation and the …
Interactively assessing disentanglement in GANs
Generative adversarial networks (GAN) have witnessed tremendous growth in recent years,
demonstrating wide applicability in many domains. However, GANs remain notoriously …
demonstrating wide applicability in many domains. However, GANs remain notoriously …
Evaluation is key: a survey on evaluation measures for synthetic time series
Synthetic data generation describes the process of learning the underlying distribution of a
given real dataset in a model, which is, in turn, sampled to produce new data objects still …
given real dataset in a model, which is, in turn, sampled to produce new data objects still …
Visualizing temperature trends: Higher sensitivity to trend direction with single-hue palettes.
Abstract Design plays a key role in the interpretability of complex visualizations. Many
applied domains utilize large quantities of data to make predictions, ranging from maps …
applied domains utilize large quantities of data to make predictions, ranging from maps …
[SoK] The great GAN bake Off, an extensive systematic evaluation of generative adversarial network architectures for time series synthesis
There is no standard approach to compare the success ofdifferent neural network
architectures utilized for time seriessynthesis. This hinders the evaluation and decision …
architectures utilized for time seriessynthesis. This hinders the evaluation and decision …
[PDF][PDF] [SoK] The Great GAN Bake Off, An Extensive Systematic Evaluation of Generative
M Leznik, A Lochner, S Wesner - Journal of Systems Research, 2 …, 2022 - researchgate.net
There is no standard approach to compare the success of different neural network
architectures utilized for time series synthesis. This hinders the evaluation and decision …
architectures utilized for time series synthesis. This hinders the evaluation and decision …