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 image inpainting or autonomous vehicles and robots.

Data and Resources

Cite this as

Marcin Przewi˛e´zlikowski, Marek ´Smieja, Łukasz Struski, Jacek Tabor (2024). Dataset: MisConv: Convolutional Neural Networks for Missing Data. https://doi.org/10.57702/t37uhocd

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Author Marcin Przewi˛e´zlikowski
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Marek ´Smieja
Łukasz Struski
Jacek Tabor
Homepage https://github.com/mprzewie/dmfa_