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Objective/Area Ref. Synthesize data [126] [127] MNIST and Cocaine-Opioid and Alcohol-Cannabis datasets (NIH- funded project) - Reconstruction of missing data for multimodal datasets. The proposed model is based on a combination of a denoising autoencoder and a variant of a generative adversarial network. It obtains better results than alternatives models such as: matrix factorization, multimodal autoencoder, pix2pix and CycleGAN - This work can be considered aligned (but not strictly similar) with the present thesis work, but it requires a training process and a network both more complex. [128] [129] [131] MINIST and Frey Face datasets QASent and WikiQA datasets. - First application of VAE to image generation - Text generation variational autoencoder, conditioned on an input text. MNIST -Reconstruction of missing parts of digits of the MNIST dataset using a VAE and a variant of principal component analysis (PCA). The model based on VAE provides the best reconstruction of the missing parts. It does not employ a conditional VAE. Dataset Scope Data collected from sensors deployed in the Intel Berkeley Research Laboratory -They propose a method to recover missing (incomplete) data from sensors in IoT networks using data obtained from related sensors. The method used is based on a probabilistic matrix factorization and it is more applicable to the recovery of continuous features [130] MINIST, CIFAR- 10 and Toronto Face Database. - First application of Generative Adversarial Networks to image generation [132] [121] Biodegradability, Mutagenesis, Airbnb, Rossmann and Telstra. All open-source datasets. - Generative model for relational data in general. They fit the probability distribution for the columns data using the Kolmogorov-Smirnov test as a measure of goodness of fit to some predefined distributions. They use a Gaussian Copula to model the covariance between different columns. Yahoo Answer and Yelp15 review datasets - Text generation with a VAE and a dilated CNN as the decoder. Table 5. Synthetic data generation - related works Doctoral Thesis: Novel applications of Machine Learning to NTAP - 39PDF Image | Novel applications of Machine Learning to Network Traffic Analysis
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