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Found 6 papers, 0 papers with code
Dynamics of Fourier Modes in Torus Generative Adversarial Networks
By studying the dynamics of the truncated Fourier series for the continuous Alternating Gradient Descend algorithm, we are able to approximate the real flow and to identify the main features of the convergence of the GAN.
Data Augmentation techniques in time series domain: A survey and taxonomy
With the latest advances in Deep Learning-based generative models, it has not taken long to take advantage of their remarkable performance in the area of time series.
Improving the quality of generative models through Smirnov transformation
In sharp contrast with previous works, our activation function provides a more general approach that deals not only with the replication of categorical variables but with any type of data distribution (continuous or discrete).
Synthetic flow-based cryptomining attack generation through Generative Adversarial Networks
Data privacy is appearing more and more as a strong requirement when processing such network data, which suggests to find solutions where synthetic data can fully replace real data.
Regularized Greedy Column Subset Selection
The Column Subset Selection Problem provides a natural framework for unsupervised feature selection.
Using Machine Learning to Detect Noisy Neighbors in 5G Networks
5G networks are expected to be more dynamic and chaotic in their structure than current networks.
