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cs.LG2019
Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training
Harrison Nguyen, Simon Luo, Fabio Ramos
Magnetic Resonance Imaging (MRI) of the brain can come in the form of different modalities such as T1-weighted and Fluid Attenuated Inversion Recovery (FLAIR) which has been used t…
cs.LG2019
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
Pantelis Elinas, Edwin V. Bonilla, Louis Tiao
We propose a framework that lifts the capabilities of graph convolutional networks (GCNs) to scenarios where no input graph is given and increases their robustness to adversarial a…