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Incomplete MNIST dataset
The dataset consists of images with missing data, where the missing regions are simulated using different techniques such as square, trapezoid, and noise. -
MisConv: Convolutional Neural Networks for Missing Data
Processing of missing data by modern neural networks, such as CNNs, remains a fundamental, yet unsolved challenge, which naturally arises in many practical applications, like... -
VAEs in the Presence of Missing Data
Real world datasets often contain entries with missing elements e.g. in a medical dataset, a patient is unlikely to have taken all possible diagnostic tests.